wenig
This commit is contained in:
chk
@@ -1,6 +1,23 @@
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{
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"_label": "todo3_2026-06-11",
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"coordinateSystem": {"handedness": "right", "x": "right", "y": "backward", "z": "up"},
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"units": {"length": "mm", "rotation": "degree"},
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"units": {"_owner": "appRobotDriver", "length": "mm", "rotation": "degree"},
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"kinematics": {
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"_owner": "appRobotDriver",
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"type": "arm3segmentlinearx"
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},
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"motion": {
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"_owner": "appRobotDriver",
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"defaultFeedrate": 2300,
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"speedMode": "legacy",
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"speedModeOptions": ["legacy", "correct"]
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},
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"controllers": {
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"_owner": "appRobotDriver",
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"base": { "ip": "fluidNcBase.local", "port": 2300, "protocol": "telnet", "axes": ["x", "y", "z"] },
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"elbow": { "ip": "fluidNcEllbow.local", "port": 5000, "protocol": "telnet", "axes": ["a", null, null] },
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"hand": { "ip": "fluidNcHand.local", "port": 5000, "protocol": "telnet", "axes": ["c", "e", "b"] }
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},
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"vision_config": {"MarkerType": "DICT_4X4_250", "MarkerSize": 0.025},
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"renderingInfo": {
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"width": 1280,
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@@ -163,6 +180,7 @@
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"normal_flip_weight": 0.05
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},
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"links": {
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"_owner": "appRobotDriver",
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"Board": {
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"parent": null,
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"size": [1000, 200, 25],
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@@ -273,7 +291,9 @@
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"axis": [1, 0, 0],
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"origin": [0, 0, 16],
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"rotation": [0, 0, 0],
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"variable": "x"
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"variable": "x",
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"feedrate": 2000,
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"controller": "base"
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},
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"skeleton": {"from": [0, 108, 45], "to": [110, 108, 45], "radius": 4, "color": [0.2, 0.8, 0.2]},
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"markers": [],
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@@ -297,7 +317,9 @@
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"axis": [-1, 0, 0],
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"origin": [110, 108, 45],
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"rotation": [0, 0, 0],
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"variable": "y"
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"variable": "y",
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"feedrate": 2300,
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"controller": "base"
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},
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"skeleton": {"from": [0, 0, 0], "to": [0, -250, 0], "radius": 4, "color": [0.2, 0.2, 0.9]},
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"markers": [
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@@ -327,7 +349,9 @@
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"axis": [-1, 0, 0],
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"origin": [0, -250, 0],
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"rotation": [0, 0, 0],
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"variable": "z"
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"variable": "z",
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"feedrate": 2300,
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"controller": "base"
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},
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"skeleton": {"from": [0, 0, 0], "to": [90, 0, 0], "radius": 4, "color": [0.9, 0.2, 0.2]},
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"model": [
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@@ -358,7 +382,9 @@
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"axis": [0, -1, 0],
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"origin": [90, 0, 0],
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"rotation": [0, 0, 0],
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"variable": "a"
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"variable": "a",
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"feedrate": 2300,
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"controller": "elbow"
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},
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"skeleton": {"from": [0, 0, 0], "to": [0, -250, 0], "radius": 4, "color": [0.95, 0.85, 0.2]},
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"model": [
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@@ -390,7 +416,9 @@
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"axis": [1, 0, 0],
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"origin": [0, -250, 0],
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"rotation": [0, 0, 0],
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"variable": "b"
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"variable": "b",
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"feedrate": 2300,
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"controller": "hand"
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},
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"skeleton": {"from": [0, 0, 0], "to": [0, -35, 0], "radius": 4, "color": [0.95, 0.55, 0.15]}
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},
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@@ -404,7 +432,9 @@
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"axis": [0, -1, 0],
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"origin": [0, 0, 0],
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"rotation": [0, 0, 0],
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"variable": "c"
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"variable": "c",
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"feedrate": 2300,
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"controller": "hand"
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},
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"skeleton": {"from": [-50, -35, 0], "to": [50, -35, 0], "radius": 7, "color": [0.95, 0.2, 0.2]}
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},
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@@ -419,7 +449,9 @@
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"axis": [1, 0, 0],
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"origin": [4, -35, 0],
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"rotation": [0, 0, 0],
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"variable": "e"
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"variable": "e",
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"feedrate": 2000,
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"controller": "hand"
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},
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"skeleton": {"from": [0, 0, 0], "to": [0, -60, 0], "radius": 4, "color": [0.2, 0.8, 0.2]},
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"markers": [
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@@ -447,7 +479,9 @@
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"axis": [-1, 0, 0],
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"origin": [-4, -35, 0],
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"rotation": [0, 0, 0],
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"variable": "e"
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"variable": "e",
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"feedrate": 2000,
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"controller": "hand"
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},
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"skeleton": {"from": [0, 0, 0], "to": [0, -60, 0], "radius": 4, "color": [0.2, 0.8, 0.2]},
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"markers": [
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BIN
data/testPictures/calibration_cam0.npz
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data/testPictures/calibration_cam0.npz
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data/testPictures/calibration_cam1.npz
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data/testPictures/calibration_cam1.npz
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data/testPictures/calibration_cam2.npz
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data/testPictures/calibration_cam2.npz
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data/testPictures/cam0_hires_1781074183695.jpg
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data/testPictures/cam0_hires_1781074183695.jpg
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data/testPictures/cam1_hires_1781074183695.jpg
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data/testPictures/cam1_hires_1781074183695.jpg
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After Width: | Height: | Size: 66 KiB |
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data/testPictures/cam2_hires_1781074183695.jpg
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data/testPictures/cam2_hires_1781074183695.jpg
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After Width: | Height: | Size: 221 KiB |
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data/testPictures/robot_1781069752019.json
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data/testPictures/robot_1781069752019.json
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@@ -0,0 +1,433 @@
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{
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"coordinateSystem": {"handedness": "right", "x": "right", "y": "backward", "z": "up"},
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"units": {"length": "mm", "rotation": "degree"},
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"vision_config": {"MarkerType": "DICT_4X4_250", "MarkerSize": 0.025},
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"renderingInfo": {
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"width": 1280,
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"height": 720,
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"renderDefaults": {"width": 1280, "height": 720, "dofFStop": 11},
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"cameraPosition__1": [-10, -800, 500],
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"cameraPosition__2": [-500, 300, 1200],
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"cameraPosition__3": [-200, -900, 200],
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"cameraPosition__4": [1200, 200, 300],
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"cameraPosition_a": [-300, -800, 500],
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"cameraPosition": [-200, 200, 1400],
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"cameraPosition_c": [600, -500, 600],
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"cameraTarget": [200, -200, 180],
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"cameraUpVector": [0, 0, 1],
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"lightPosition": [-500, -500, 500],
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"lightTarget": [0, 0, 0],
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"lightUpVector": [0, 0, 1],
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"metric": "mm",
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"showSkeleton": true,
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"showMarkers": true,
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"backgroundColor": [0.7, 0.85, 1.0],
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"backgroundStrength": 0.2,
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"sunEnergy": 0.35,
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"areaEnergy": 120,
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"exposure": -1.5,
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"lensDirt": true,
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"lensDirtStrength": 0.08,
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"dofEnabled": true,
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"dofFStop": 11.0,
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"arucoDust": true,
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"arucoDustStrength": 1.6,
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"markerOffsetMaxMm": 4.0,
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"markerOffsetSeed": 0,
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"markerRotationMaxDeg": 3,
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"motionBlur": true,
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"motionBlurMaxPx": 5.5,
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"focalErrorPct": 0.5,
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"principalErrorPx": 3.0,
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"residualDistortion": [0.02, -0.01],
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"localizedBlur": false,
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"localizedBlurStrength": 0.15,
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"vignette": true,
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"vignetteStrength": 0.08,
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"sensorNoise": true,
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"sensorNoiseStrength": 0.01,
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"lensDistortion": true,
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"lensDistortionStrength": 0.002,
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"materials": {
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"wood": {"baseColor": [0.72, 0.52, 0.33], "roughness": 0.85, "metallic": 0.0},
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"plaWhite": {"baseColor": [0.95, 0.95, 0.95], "roughness": 0.45, "metallic": 0.0},
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"steel": {"baseColor": [0.72, 0.72, 0.75], "roughness": 0.25, "metallic": 1.0},
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"powderCoatBlue": {"baseColor": [0.15, 0.25, 0.7], "roughness": 0.55, "metallic": 0.0},
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"defaultPlastic": {"baseColor": [0.95, 0.95, 0.95], "roughness": 0.4, "metallic": 0.0},
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"skeletonRed": {"baseColor": [0.85, 0.2, 0.2], "roughness": 0.35, "metallic": 0.0},
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"markerBlack": {"baseColor": [0.04, 0.04, 0.04], "roughness": 0.8, "metallic": 0.0}
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},
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"skeletonDefaults": {"radius": 4, "color": [0.85, 0.2, 0.2]},
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||||
"markerDefaults": {"size": 25, "thickness": 1, "color": [0.04, 0.04, 0.04]},
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||||
"defaultPosition": {"x": 80, "y": 20, "z": 80, "a": -120, "b": 23, "c": 9, "e": 3}
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},
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||||
"defaultPosition__": {"x": 10, "y": 4, "z": 20, "a": 10, "b": 2, "c": 9, "e": 1},
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||||
"defaultPosition": {"x": 50, "y": 4, "z": 176, "a": 20, "b": 60, "c": 9, "e": 5},
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||||
"recognized": {"x": null, "y": null, "z": null, "a": null, "b": null, "c": null, "e": null},
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||||
"constraint_rules": {
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||||
"rigid_distance": {"enabled": true, "mode": "mst", "weight": 1.0},
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||||
"joint_axis_projection": {"enabled": true, "max_pairs": 2, "weight": 0.35},
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||||
"chain_axis_projection": {"enabled": false, "max_depth": 3, "max_pairs": 2, "weight": 0.15},
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||||
"axis_alignment_threshold": 0.95
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},
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||||
"observation_weighting": {"enabled": true, "distance_weight": true, "marker_size_weight": true, "view_angle_weight": true},
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||||
"multiview_calculation": {
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||||
"combine_mode": "mean",
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||||
"size_ref_px": 50.0,
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||||
"border_ref_px": 120.0,
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||||
"center_ref_norm": 0.01,
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||||
"sharpness_ref": 2500.0,
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||||
"homography_ref": 0.18,
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||||
"size_factor": 0.3,
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||||
"aspect_factor": 0.3,
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||||
"border_factor": 0.01,
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||||
"center_factor": 0.01,
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||||
"sharpness_factor": 0.5,
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||||
"homography_factor": 0.2,
|
||||
"normal_visibility_factor": 0.01,
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||||
"spin_factor": 0.3,
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||||
"weight_floor": 0.3
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},
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||||
"pose_estimation": {
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||||
"method": "hybrid",
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||||
"marker_observation": "corner_pose",
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||||
"use_normals": true,
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||||
"normal_weight": 100.0,
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||||
"robust_loss": "huber",
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||||
"huber_delta_mm": 8.0,
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"max_iterations": 200,
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||||
"min_cameras_per_marker": 2,
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||||
"finger_block_joints": ["b", "c", "e"],
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"per_link_method": {}
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},
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"robot_test_poses": {
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"4": {"x": 70, "y": 50, "z": -70, "a": 120, "b": 50, "c": 30, "e": 20},
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"5": {"x": 180, "y": 86, "z": -120, "a": -60, "b": 22, "c": 91, "e": 10},
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||||
"6": {"x": 80, "y": 20, "z": 80, "a": -120, "b": 23, "c": 9, "e": 3},
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||||
"7": {"x": 30, "y": -2, "z": 95, "a": 20, "b": 23, "c": 9, "e": 9},
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||||
"8": {"x": 50, "y": -2, "z": 95, "a": 20, "b": 60, "c": 9, "e": 3},
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"9": {"x": 60, "y": -2, "z": 95, "a": 200, "b": 60, "c": 9, "e": 8},
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"9a": {
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"x": 60,
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"y": -2,
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"z": 95,
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"a": 200,
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"b": 60,
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"c": 9,
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"e": 8,
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"rendering": {"width": 1440, "height": 1080, "dofFStop": 11}
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},
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"9b": {
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"x": 60,
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"y": -2,
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"z": 95,
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"a": 200,
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"b": 60,
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"c": 9,
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"e": 8,
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"rendering": {"width": 4896, "height": 3264, "dofFStop": 5.6}
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},
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"10": {"x": 120, "y": 60, "z": -110, "a": 20, "b": 30, "c": 180, "e": 4},
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"11": {"x": 50, "y": 4, "z": 176, "a": 20, "b": 60, "c": 9, "e": 5},
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"12": {"x": 50, "y": 0, "z": 178, "a": 210, "b": 80, "c": 90, "e": 6}
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},
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"test_camera_positions": {
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"a": [-300, -800, 800],
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"b": [300, -900, 1200],
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"c": [300, -900, 400],
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||||
"d": [700, -800, 400],
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"e": [1200, -900, 400],
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"f": [500, -300, 1400],
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||||
"g": [-200, 200, 1400]
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||||
},
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"test_camera_targets": {
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||||
"a": [210, -100, 180],
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"b": [310, -80, 180],
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||||
"c": [210, -100, 150],
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||||
"d": [210, -100, 150],
|
||||
"e": [210, -100, 50],
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||||
"f": [200, -200, 180],
|
||||
"g": [200, -200, 180]
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||||
},
|
||||
"movements": {"x": null, "y": null, "z": null, "a": null, "b": null, "c": null, "e": null},
|
||||
"state_pose_params": {
|
||||
"numbers_of_Elements_to_consider_start": 3,
|
||||
"numbers_of_Elements_to_consider_final": 5,
|
||||
"solver_in_between_geometrical": false,
|
||||
"solver_after_geometrical": false,
|
||||
"geometric_passes_per_stage": 2,
|
||||
"revolute_search_coarse_deg": 5.0,
|
||||
"revolute_search_fine_deg": 1.0,
|
||||
"root_pose_min_markers": 3,
|
||||
"use_marker_normals_flip_tiebreak": true,
|
||||
"normal_flip_weight": 0.05
|
||||
},
|
||||
"links": {
|
||||
"Board": {
|
||||
"parent": null,
|
||||
"size": [1000, 200, 25],
|
||||
"mountPosition": [0, 0, 0],
|
||||
"mountRotation": [0, 0, 0],
|
||||
"skeleton": {"from": [0, 0, 16], "to": [1000, 0, 16], "radius": 4, "color": [0.85, 0.2, 0.2]},
|
||||
"markers": [
|
||||
{
|
||||
"id": 46,
|
||||
"set": "A0",
|
||||
"position": [536.71, 185.44, -27.3],
|
||||
"normal": [0, 0, 1],
|
||||
"spin": 90,
|
||||
"info": "is placed on a white paper, A0_60Arucos_25mm_Seet223.pdf, with the following marker placements:"
|
||||
},
|
||||
{"id": 47, "set": "A0", "position": [344.23, -286.54, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 48, "set": "A0", "position": [688.69, -320.72, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 49, "set": "A0", "position": [1006.0, 158.33, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 50, "set": "A0", "position": [573.41, 211.86, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 51, "set": "A0", "position": [167.8, -172.08, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 52, "set": "A0", "position": [94.68, 208.66, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 53, "set": "A0", "position": [486.25, 212.24, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 54, "set": "A0", "position": [342.27, -330.59, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 55, "set": "A0", "position": [283.72, -262.58, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 56, "set": "A0", "position": [498.68, 168.67, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 57, "set": "A0", "position": [602.86, -364.05, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 58, "set": "A0", "position": [50.09, -218.11, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 59, "set": "A0", "position": [626.21, -278.75, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 60, "set": "A0", "position": [434.36, 283.81, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 61, "set": "A0", "position": [-22.42, 335.83, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 62, "set": "A0", "position": [404.7, -175.1, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 63, "set": "A0", "position": [777.4, -236.15, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 64, "set": "A0", "position": [-21.27, -188.23, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 65, "set": "A0", "position": [803.39, -297.37, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 66, "set": "A0", "position": [209.75, -363.23, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 67, "set": "A0", "position": [523.07, 267.04, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 68, "set": "A0", "position": [573.73, 170.64, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 69, "set": "A0", "position": [7.61, -281.21, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 70, "set": "A0", "position": [601.87, 300.33, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 71, "set": "A0", "position": [749.75, -284.01, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 72, "set": "A0", "position": [440.99, 194.32, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 73, "set": "A0", "position": [221.73, 333.11, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 74, "set": "A0", "position": [93.78, 144.5, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 75, "set": "A0", "position": [-25.7, 194.58, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 76, "set": "A0", "position": [685.21, 166.8, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 77, "set": "A0", "position": [18.19, 191.57, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 78, "set": "A0", "position": [823.11, -344.38, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 79, "set": "A0", "position": [312.3, -159.11, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 80, "set": "A0", "position": [863.59, -335.92, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 81, "set": "A0", "position": [132.14, 169.03, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 82, "set": "A0", "position": [219.16, 297.24, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 83, "set": "A0", "position": [44.16, 339.22, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 84, "set": "A0", "position": [407.49, 258.42, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 85, "set": "A0", "position": [504.58, -312.75, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 86, "set": "A0", "position": [362.89, 292.01, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 87, "set": "A0", "position": [943.63, -245.76, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 88, "set": "A0", "position": [765.87, 316.04, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 89, "set": "A0", "position": [988.02, -369.14, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 90, "set": "A0", "position": [643.17, 316.43, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 91, "set": "A0", "position": [723.35, 328.05, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 92, "set": "A0", "position": [645.09, -184.84, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 93, "set": "A0", "position": [934.88, 143.6, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 94, "set": "A0", "position": [875.7, 173.65, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 95, "set": "A0", "position": [186.04, -274.07, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 96, "set": "A0", "position": [369.77, -186.49, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 97, "set": "A0", "position": [304.35, -359.67, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 98, "set": "A0", "position": [575.27, 315.06, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 99, "set": "A0", "position": [959.16, -321.55, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 100, "set": "A0", "position": [803.25, 172.36, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 101, "set": "A0", "position": [117.7, 298.66, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 102, "set": "A0", "position": [649.69, -223.0, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 103, "set": "A0", "position": [105.71, -187.71, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 104, "set": "A0", "position": [826.71, 239.16, -27.3], "normal": [0, 0, 1], "spin": 90},
|
||||
{"id": 105, "set": "A0", "position": [524.84, -266.25, -27.3], "normal": [0, 0, 1], "spin": 90}
|
||||
],
|
||||
"model": [
|
||||
{
|
||||
"stlFile": "surfaces/Board.stl",
|
||||
"originOfModel": [0, 0, 0],
|
||||
"rotationOfModelDegree": [0, 0, -90],
|
||||
"material": "wood"
|
||||
},
|
||||
{
|
||||
"stlFile": "surfaces/BoardRail.stl",
|
||||
"originOfModel": [0, 0, 0],
|
||||
"rotationOfModelDegree": [0, 0, -90],
|
||||
"material": "steel"
|
||||
}
|
||||
]
|
||||
},
|
||||
"Base": {
|
||||
"parent": "Board",
|
||||
"size": [150, 200, 150],
|
||||
"mountPosition": [0, 0, 0],
|
||||
"mountRotation": [0, 0, 0],
|
||||
"jointToParent": {
|
||||
"name": "Slider",
|
||||
"type": "linear",
|
||||
"axis": [1, 0, 0],
|
||||
"origin": [0, 0, 16],
|
||||
"rotation": [0, 0, 0],
|
||||
"variable": "x"
|
||||
},
|
||||
"skeleton": {"from": [0, 108, 45], "to": [110, 108, 45], "radius": 4, "color": [0.2, 0.8, 0.2]},
|
||||
"markers": [],
|
||||
"model": [
|
||||
{
|
||||
"stlFile": "surfaces/Base.stl",
|
||||
"originOfModel": [-30, 0, -35],
|
||||
"rotationOfModelDegree": [0, 0, 0],
|
||||
"material": "plaWhite"
|
||||
}
|
||||
]
|
||||
},
|
||||
"Arm1": {
|
||||
"parent": "Base",
|
||||
"size": [70, 250, 70],
|
||||
"mountPosition": [0, 0, 0],
|
||||
"mountRotation": [0, 0, 0],
|
||||
"jointToParent": {
|
||||
"name": "Joint1",
|
||||
"type": "revolute",
|
||||
"axis": [-1, 0, 0],
|
||||
"origin": [110, 108, 45],
|
||||
"rotation": [0, 0, 0],
|
||||
"variable": "y"
|
||||
},
|
||||
"skeleton": {"from": [0, 0, 0], "to": [0, -250, 0], "radius": 4, "color": [0.2, 0.2, 0.9]},
|
||||
"markers": [ ],
|
||||
"model": [
|
||||
{
|
||||
"stlFile": "surfaces/Holm.stl",
|
||||
"originOfModel__": [-25, 29, -28.5],
|
||||
"originOfModel": [-29, 25, 28.5],
|
||||
"rotationOfModelDegree__": [0, 0, 0],
|
||||
"rotationOfModelDegree": [180, 0, -90],
|
||||
"material": "powderCoatBlue"
|
||||
}
|
||||
]
|
||||
},
|
||||
"Ellbow": {
|
||||
"parent": "Arm1",
|
||||
"mountPosition": [0, 0, 0],
|
||||
"mountRotation": [0, 0, 0],
|
||||
"jointToParent": {
|
||||
"name": "Joint2",
|
||||
"type": "revolute",
|
||||
"axis": [-1, 0, 0],
|
||||
"origin": [0, -250, 0],
|
||||
"rotation": [0, 0, 0],
|
||||
"variable": "z"
|
||||
},
|
||||
"skeleton": {"from": [0, 0, 0], "to": [90, 0, 0], "radius": 4, "color": [0.9, 0.2, 0.2]},
|
||||
"model": [
|
||||
{
|
||||
"stlFile": "surfaces/Ellebogen.stl",
|
||||
"originOfModel": [90, 0, 0],
|
||||
"rotationOfModelDegree": [0, -90, -90],
|
||||
"material": "defaultPlastic"
|
||||
}
|
||||
],
|
||||
"markers": [
|
||||
]
|
||||
},
|
||||
"Arm2": {
|
||||
"parent": "Ellbow",
|
||||
"mountPosition": [0, 0, 0],
|
||||
"mountRotation": [0, 0, 0],
|
||||
"jointToParent": {
|
||||
"name": "Joint3",
|
||||
"type": "revolute",
|
||||
"axis": [0, -1, 0],
|
||||
"origin": [90, 0, 0],
|
||||
"rotation": [0, 0, 0],
|
||||
"variable": "a"
|
||||
},
|
||||
"skeleton": {"from": [0, 0, 0], "to": [0, -250, 0], "radius": 4, "color": [0.95, 0.85, 0.2]},
|
||||
"model": [
|
||||
{
|
||||
"stlFile": "surfaces/Unterarm.stl",
|
||||
"originOfModel": [0, -250, 0],
|
||||
"rotationOfModelDegree": [180, 0, -90],
|
||||
"material": "defaultPlastic"
|
||||
}
|
||||
],
|
||||
"markers": [
|
||||
]
|
||||
},
|
||||
"Hand": {
|
||||
"parent": "Arm2",
|
||||
"mountPosition": [0, 0, 0],
|
||||
"mountRotation": [0, 0, 0],
|
||||
"jointToParent": {
|
||||
"name": "Joint4",
|
||||
"type": "revolute",
|
||||
"axis": [1, 0, 0],
|
||||
"origin": [0, -250, 0],
|
||||
"rotation": [0, 0, 0],
|
||||
"variable": "b"
|
||||
},
|
||||
"skeleton": {"from": [0, 0, 0], "to": [0, -35, 0], "radius": 4, "color": [0.95, 0.55, 0.15]}
|
||||
},
|
||||
"Palm": {
|
||||
"parent": "Hand",
|
||||
"mountPosition": [0, 0, 0],
|
||||
"mountRotation": [0, 0, 0],
|
||||
"jointToParent": {
|
||||
"name": "Joint3",
|
||||
"type": "revolute",
|
||||
"axis": [0, -1, 0],
|
||||
"origin": [0, 0, 0],
|
||||
"rotation": [0, 0, 0],
|
||||
"variable": "c"
|
||||
},
|
||||
"skeleton": {"from": [-50, -35, 0], "to": [50, -35, 0], "radius": 7, "color": [0.95, 0.2, 0.2]}
|
||||
},
|
||||
"FingerA": {
|
||||
"parent": "Palm",
|
||||
"size": [80, 60, 20],
|
||||
"mountPosition": [0, 0, 0],
|
||||
"mountRotation": [0, 0, 0],
|
||||
"jointToParent": {
|
||||
"name": "Slider",
|
||||
"type": "linear",
|
||||
"axis": [1, 0, 0],
|
||||
"origin": [4, -35, 0],
|
||||
"rotation": [0, 0, 0],
|
||||
"variable": "e"
|
||||
},
|
||||
"skeleton": {"from": [0, 0, 0], "to": [0, -60, 0], "radius": 4, "color": [0.2, 0.8, 0.2]},
|
||||
"markers": [
|
||||
],
|
||||
"model": [
|
||||
{
|
||||
"stlFile": "surfaces/Finger.stl",
|
||||
"originOfModel": [24, 0, -9.1],
|
||||
"rotationOfModelDegree": [90, -90, 0],
|
||||
"material": "defaultPlastic"
|
||||
}
|
||||
]
|
||||
},
|
||||
"FingerB": {
|
||||
"parent": "Palm",
|
||||
"size": [80, 60, 20],
|
||||
"mountPosition": [0, 0, 0],
|
||||
"mountRotation": [0, 0, 0],
|
||||
"jointToParent": {
|
||||
"name": "Slider",
|
||||
"type": "linear",
|
||||
"axis": [-1, 0, 0],
|
||||
"origin": [-4, -35, 0],
|
||||
"rotation": [0, 0, 0],
|
||||
"variable": "e"
|
||||
},
|
||||
"skeleton": {"from": [0, 0, 0], "to": [0, -60, 0], "radius": 4, "color": [0.2, 0.8, 0.2]},
|
||||
"markers": [
|
||||
],
|
||||
"model": [
|
||||
{
|
||||
"stlFile": "surfaces/Finger.stl",
|
||||
"originOfModel": [-24, 0, 9.1],
|
||||
"rotationOfModelDegree": [90, 90, 0],
|
||||
"material": "defaultPlastic"
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -351,6 +351,12 @@ def main():
|
||||
required=True
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'--saveDebugImage',
|
||||
action='store_true',
|
||||
help='Speichert ein Debug-JPG mit eingezeichneten Marker-Rahmen'
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
out_dir = resolve_path(args.outDir)
|
||||
@@ -404,6 +410,9 @@ def main():
|
||||
detector_tuple
|
||||
)
|
||||
|
||||
# ids_raw: original numpy array für drawDetectedMarkers
|
||||
ids_raw = ids
|
||||
|
||||
detections = []
|
||||
|
||||
# --------------------------------------------------------
|
||||
@@ -601,6 +610,25 @@ def main():
|
||||
|
||||
print(f'Saved: {out_json}')
|
||||
|
||||
# --------------------------------------------------------
|
||||
# Debug-Bild mit Marker-Rahmen
|
||||
# --------------------------------------------------------
|
||||
|
||||
if args.saveDebugImage:
|
||||
|
||||
debug_img = image.copy()
|
||||
|
||||
if corners_list and ids_raw is not None:
|
||||
cv2.aruco.drawDetectedMarkers(debug_img, corners_list, ids_raw)
|
||||
|
||||
debug_path = os.path.join(
|
||||
out_dir,
|
||||
f'{input_base}_debug.jpg'
|
||||
)
|
||||
|
||||
cv2.imwrite(debug_path, debug_img)
|
||||
print(f'Saved debug: {debug_path}')
|
||||
|
||||
|
||||
# ------------------------------------------------------------
|
||||
|
||||
|
||||
424
test/jRun.py
Normal file
424
test/jRun.py
Normal file
@@ -0,0 +1,424 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
jRun.py – Test-Pipeline: detect → camera-pose → ArUco-CSV
|
||||
|
||||
Ablauf:
|
||||
1. pipeline/1_detect_aruco_observations.py pro Bild → test/temp/
|
||||
2. pipeline/2_estimate_camera_from_observations.py pro Bild → test/temp/
|
||||
3. Positionen + Normalen per solvePnP aus Beobachtungen ableiten,
|
||||
über alle Kameras mitteln, nach ID sortieren
|
||||
4. test/temp/detections.csv schreiben: id, set, x, y, z, nx, ny, nz
|
||||
|
||||
Einheiten: x/y/z in mm (Weltframe des Roboters), nx/ny/nz dimensionslos.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import csv
|
||||
import glob
|
||||
import json
|
||||
import os
|
||||
import re
|
||||
import subprocess
|
||||
import sys
|
||||
from typing import Dict, List, Optional, Tuple
|
||||
|
||||
import cv2
|
||||
import numpy as np
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Pfade
|
||||
# ---------------------------------------------------------------------------
|
||||
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
|
||||
PROJECT_ROOT = os.path.dirname(SCRIPT_DIR)
|
||||
PIPELINE_DIR = os.path.join(PROJECT_ROOT, "pipeline")
|
||||
DATA_DIR = os.path.join(PROJECT_ROOT, "data", "testPictures")
|
||||
TEMP_DIR = os.path.join(SCRIPT_DIR, "temp")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Hilfsfunktionen – Dateien
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def find_images() -> List[str]:
|
||||
return sorted(glob.glob(os.path.join(DATA_DIR, "cam*_hires_*.jpg")))
|
||||
|
||||
|
||||
def cam_id_from_path(img_path: str) -> str:
|
||||
m = re.match(r"(cam\d+)_", os.path.basename(img_path))
|
||||
if not m:
|
||||
raise ValueError(f"Kein Camera-ID in Dateiname: {img_path}")
|
||||
return m.group(1)
|
||||
|
||||
|
||||
def npz_path(cam_id: str) -> str:
|
||||
p = os.path.join(DATA_DIR, f"calibration_{cam_id}.npz")
|
||||
if not os.path.exists(p):
|
||||
raise FileNotFoundError(f"Kalibrierung nicht gefunden: {p}")
|
||||
return p
|
||||
|
||||
|
||||
def find_robot_json() -> str:
|
||||
candidates = glob.glob(os.path.join(DATA_DIR, "robot*.json"))
|
||||
if not candidates:
|
||||
raise FileNotFoundError(f"Kein robot*.json in {DATA_DIR}")
|
||||
return sorted(candidates)[0]
|
||||
|
||||
|
||||
def detection_json_path(img_path: str) -> str:
|
||||
base = os.path.splitext(os.path.basename(img_path))[0]
|
||||
return os.path.join(TEMP_DIR, f"{base}_aruco_detection.json")
|
||||
|
||||
|
||||
def camera_pose_json_path(img_path: str) -> str:
|
||||
base = os.path.splitext(os.path.basename(img_path))[0]
|
||||
return os.path.join(TEMP_DIR, f"{base}_camera_pose.json")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Subprocess-Wrapper
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def run_step(cmd: List[str]) -> None:
|
||||
print(f"\n>>> {' '.join(cmd)}")
|
||||
r = subprocess.run(cmd, text=True)
|
||||
if r.returncode != 0:
|
||||
raise RuntimeError(f"Befehl fehlgeschlagen (exit {r.returncode})")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Marker-Klassifizierung aus robot.json
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def load_marker_set_map(robot_path: str) -> Dict[int, str]:
|
||||
"""
|
||||
Gibt marker_id -> Set-Label zurück.
|
||||
'set'-Marker → set_name (z.B. 'Brett', 'A0')
|
||||
Arm/Loose → Link-Name
|
||||
"""
|
||||
if PIPELINE_DIR not in sys.path:
|
||||
sys.path.insert(0, PIPELINE_DIR)
|
||||
|
||||
# Import erst nach sys.path-Erweiterung
|
||||
from marker_sets import classify_markers # noqa: PLC0415
|
||||
|
||||
with open(robot_path, "r", encoding="utf-8") as f:
|
||||
robot_data = json.load(f)
|
||||
|
||||
classification = classify_markers(robot_data)
|
||||
result: Dict[int, str] = {}
|
||||
for mid, info in classification.items():
|
||||
if info.role == "set" and info.set_name:
|
||||
result[mid] = info.set_name
|
||||
else:
|
||||
result[mid] = info.link
|
||||
return result
|
||||
|
||||
|
||||
def load_a0_reference(robot_path: str) -> Dict[int, np.ndarray]:
|
||||
"""
|
||||
Welt-Referenz (x, y) in mm für die A0-Marker aus robot.json.
|
||||
|
||||
Nur die A0-Marker definieren (momentan) die Welt-Koordinaten, daher wird
|
||||
der dxy-Abgleich ausschließlich auf sie beschränkt. Position steht im
|
||||
Board-Frame = Welt-Frame (Board ist Wurzel-Link bei [0,0,0]).
|
||||
"""
|
||||
if PIPELINE_DIR not in sys.path:
|
||||
sys.path.insert(0, PIPELINE_DIR)
|
||||
|
||||
from marker_sets import classify_markers # noqa: PLC0415
|
||||
|
||||
with open(robot_path, "r", encoding="utf-8") as f:
|
||||
robot_data = json.load(f)
|
||||
|
||||
ref: Dict[int, np.ndarray] = {}
|
||||
for mid, info in classify_markers(robot_data).items():
|
||||
if info.role == "set" and info.set_name == "A0":
|
||||
ref[mid] = np.array(info.position[:2], dtype=float)
|
||||
return ref
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Positionen + Normalen per solvePnP
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _marker_local_corners(marker_size_m: float) -> np.ndarray:
|
||||
h = marker_size_m / 2.0
|
||||
return np.array([
|
||||
[-h, h, 0.0],
|
||||
[ h, h, 0.0],
|
||||
[ h, -h, 0.0],
|
||||
[-h, -h, 0.0],
|
||||
], dtype=np.float32)
|
||||
|
||||
|
||||
def estimate_marker_poses(
|
||||
det_json: dict,
|
||||
pose_json: dict,
|
||||
) -> Dict[int, Tuple[np.ndarray, np.ndarray]]:
|
||||
"""
|
||||
Gibt pro erkannter Marker-ID: (pos_mm [3], normal_world [3]) zurück.
|
||||
|
||||
pos_mm: Marker-Mittelpunkt im Weltframe, Einheit mm
|
||||
normal_world: normierter Normalenvektor (Marker-Z-Achse im Weltframe)
|
||||
"""
|
||||
K = np.array(det_json["camera"]["camera_matrix"],
|
||||
dtype=np.float64).reshape(3, 3)
|
||||
D = np.array(det_json["camera"]["distortion_coefficients"],
|
||||
dtype=np.float64).reshape(-1, 1)
|
||||
marker_size_m = float(
|
||||
det_json.get("vision_config", {}).get("MarkerSize", 0.025)
|
||||
)
|
||||
|
||||
w2c = pose_json["camera_pose"]["world_to_camera"]
|
||||
R_wc = np.array(w2c["rotation_matrix"], dtype=np.float64).reshape(3, 3)
|
||||
t_wc = np.array(w2c["translation_m"], dtype=np.float64).reshape(3)
|
||||
|
||||
obj_corners = _marker_local_corners(marker_size_m)
|
||||
result: Dict[int, Tuple[np.ndarray, np.ndarray]] = {}
|
||||
|
||||
for det in det_json.get("detections", []):
|
||||
mid = int(det["marker_id"])
|
||||
corners_px = np.array(
|
||||
det["image_points_px"], dtype=np.float32
|
||||
).reshape(4, 2)
|
||||
|
||||
ok, rvec, tvec = cv2.solvePnP(
|
||||
obj_corners, corners_px,
|
||||
K.astype(np.float32), D.astype(np.float32),
|
||||
flags=cv2.SOLVEPNP_IPPE_SQUARE,
|
||||
)
|
||||
if not ok:
|
||||
ok, rvec, tvec = cv2.solvePnP(
|
||||
obj_corners, corners_px,
|
||||
K.astype(np.float32), D.astype(np.float32),
|
||||
flags=cv2.SOLVEPNP_ITERATIVE,
|
||||
)
|
||||
if not ok:
|
||||
continue
|
||||
|
||||
tvec_f = tvec.reshape(3).astype(np.float64)
|
||||
R_mc, _ = cv2.Rodrigues(rvec.reshape(3, 1))
|
||||
R_mc = R_mc.astype(np.float64)
|
||||
|
||||
# Weltframe-Position: x_world = R_wc.T @ (x_cam - t_wc)
|
||||
pos_world_m = R_wc.T @ (tvec_f - t_wc)
|
||||
|
||||
# Marker-Normale (Z-Achse) im Weltframe
|
||||
normal_cam = R_mc[:, 2]
|
||||
normal_world = R_wc.T @ normal_cam
|
||||
nlen = np.linalg.norm(normal_world)
|
||||
if nlen > 1e-9:
|
||||
normal_world /= nlen
|
||||
|
||||
result[mid] = (pos_world_m * 1000.0, normal_world)
|
||||
|
||||
return result
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Main
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def main() -> None:
|
||||
os.makedirs(TEMP_DIR, exist_ok=True)
|
||||
|
||||
images = find_images()
|
||||
if not images:
|
||||
print(f"[FEHLER] Keine cam*_hires_*.jpg in {DATA_DIR}")
|
||||
sys.exit(1)
|
||||
|
||||
robot_path = find_robot_json()
|
||||
print(f"Robot: {os.path.basename(robot_path)}")
|
||||
print(f"Bilder: {[os.path.basename(i) for i in images]}")
|
||||
print(f"Ausgabe-Ordner: {TEMP_DIR}")
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Schritt 1: ArUco-Erkennung
|
||||
# ------------------------------------------------------------------
|
||||
print("\n" + "=" * 60)
|
||||
print("Schritt 1: ArUco-Erkennung")
|
||||
print("=" * 60)
|
||||
for img in images:
|
||||
cam_id = cam_id_from_path(img)
|
||||
run_step([
|
||||
sys.executable,
|
||||
os.path.join(PIPELINE_DIR, "1_detect_aruco_observations.py"),
|
||||
"-i", img,
|
||||
"-npz", npz_path(cam_id),
|
||||
"-robot", robot_path,
|
||||
"-cameraId", cam_id,
|
||||
"-outDir", TEMP_DIR,
|
||||
"--saveDebugImage",
|
||||
])
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Schritt 2: Kamera-Positionen
|
||||
# ------------------------------------------------------------------
|
||||
print("\n" + "=" * 60)
|
||||
print("Schritt 2: Kamera-Poses")
|
||||
print("=" * 60)
|
||||
for img in images:
|
||||
run_step([
|
||||
sys.executable,
|
||||
os.path.join(PIPELINE_DIR, "2_estimate_camera_from_observations.py"),
|
||||
"-i", detection_json_path(img),
|
||||
"-robot", robot_path,
|
||||
"-outDir", TEMP_DIR,
|
||||
])
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Schritt 3: Beobachtungen zusammenführen
|
||||
# ------------------------------------------------------------------
|
||||
print("\n" + "=" * 60)
|
||||
print("Schritt 3: Positionen + Normalen")
|
||||
print("=" * 60)
|
||||
|
||||
marker_set_map = load_marker_set_map(robot_path)
|
||||
a0_ref = load_a0_reference(robot_path)
|
||||
|
||||
# mid -> Liste von (pos_mm, normal)
|
||||
observations: Dict[int, List[Tuple[np.ndarray, np.ndarray]]] = {}
|
||||
|
||||
# cam_id -> Welt-Position (mm) / QA-Metadaten
|
||||
camera_positions: Dict[str, np.ndarray] = {}
|
||||
camera_meta: Dict[str, dict] = {}
|
||||
|
||||
for img in images:
|
||||
det_path = detection_json_path(img)
|
||||
pose_path = camera_pose_json_path(img)
|
||||
|
||||
if not os.path.exists(det_path):
|
||||
print(f"[WARN] Fehlend: {det_path}")
|
||||
continue
|
||||
if not os.path.exists(pose_path):
|
||||
print(f"[WARN] Fehlend: {pose_path}")
|
||||
continue
|
||||
|
||||
with open(det_path, "r", encoding="utf-8") as f:
|
||||
det_json = json.load(f)
|
||||
with open(pose_path, "r", encoding="utf-8") as f:
|
||||
pose_json = json.load(f)
|
||||
|
||||
cam_id = cam_id_from_path(img)
|
||||
ciw = pose_json["camera_pose"]["camera_in_world"]["position_mm"]
|
||||
camera_positions[cam_id] = np.array(ciw, dtype=float)
|
||||
est = pose_json.get("estimation", {})
|
||||
camera_meta[cam_id] = {
|
||||
"rms_px": est.get("residual_rms_px"),
|
||||
"num_markers": est.get("num_used_markers"),
|
||||
}
|
||||
|
||||
cam_name = os.path.basename(img)
|
||||
poses = estimate_marker_poses(det_json, pose_json)
|
||||
print(f" {cam_name}: {len(poses)} Marker mit Pose")
|
||||
|
||||
for mid, pn in poses.items():
|
||||
observations.setdefault(mid, []).append(pn)
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Mittelwert über alle Kameras + CSV schreiben
|
||||
# ------------------------------------------------------------------
|
||||
rows = []
|
||||
for mid in sorted(observations.keys()):
|
||||
obs_list = observations[mid]
|
||||
positions = np.array([p for p, _ in obs_list])
|
||||
normals = np.array([n for _, n in obs_list])
|
||||
|
||||
pos_mean = positions.mean(axis=0)
|
||||
|
||||
n_sum = normals.sum(axis=0)
|
||||
n_norm = np.linalg.norm(n_sum)
|
||||
normal_mean = n_sum / n_norm if n_norm > 1e-9 else np.array([0.0, 0.0, 1.0])
|
||||
|
||||
set_label = marker_set_map.get(mid, "?")
|
||||
|
||||
# dxy: planarer Abgleich gegen robot.json — nur für A0 definiert
|
||||
if mid in a0_ref:
|
||||
d = pos_mean[:2] - a0_ref[mid]
|
||||
dxy = round(float(np.hypot(d[0], d[1])), 2)
|
||||
else:
|
||||
dxy = ""
|
||||
|
||||
rows.append({
|
||||
"id": mid,
|
||||
"set": set_label,
|
||||
"SeenByCount": len(obs_list),
|
||||
"x": round(float(pos_mean[0]), 2),
|
||||
"y": round(float(pos_mean[1]), 2),
|
||||
"z": round(float(pos_mean[2]), 2),
|
||||
"nx": round(float(normal_mean[0]), 4),
|
||||
"ny": round(float(normal_mean[1]), 4),
|
||||
"nz": round(float(normal_mean[2]), 4),
|
||||
"dxy": dxy,
|
||||
})
|
||||
|
||||
# Kamera-Positionen als eigene Zeilen (oben in der CSV)
|
||||
camera_rows = []
|
||||
for cam_id in sorted(camera_positions.keys()):
|
||||
pos = camera_positions[cam_id]
|
||||
camera_rows.append({
|
||||
"id": cam_id,
|
||||
"set": "CAMERA",
|
||||
"SeenByCount": "",
|
||||
"x": round(float(pos[0]), 2),
|
||||
"y": round(float(pos[1]), 2),
|
||||
"z": round(float(pos[2]), 2),
|
||||
"nx": "",
|
||||
"ny": "",
|
||||
"nz": "",
|
||||
"dxy": "",
|
||||
})
|
||||
|
||||
csv_path = os.path.join(TEMP_DIR, "detections.csv")
|
||||
fieldnames = ["id", "set", "SeenByCount", "x", "y", "z", "nx", "ny", "nz", "dxy"]
|
||||
|
||||
with open(csv_path, "w", newline="", encoding="utf-8") as f:
|
||||
writer = csv.DictWriter(f, fieldnames=fieldnames)
|
||||
writer.writeheader()
|
||||
writer.writerows(camera_rows + rows)
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Konsolenübersicht
|
||||
# ------------------------------------------------------------------
|
||||
print(f"\nGeschrieben: {csv_path} "
|
||||
f"({len(rows)} Marker + {len(camera_rows)} Kameras)\n")
|
||||
|
||||
# Kamera-Positionen + Reprojektions-RMS (schlechte Kamera erkennen)
|
||||
print("Kamera-Positionen (Welt, mm):")
|
||||
chdr = f"{'cam':>5} {'x':>9} {'y':>9} {'z':>9} {'rms_px':>7} {'#mk':>4}"
|
||||
print(chdr)
|
||||
print("-" * len(chdr))
|
||||
for cam_id in sorted(camera_positions.keys()):
|
||||
pos = camera_positions[cam_id]
|
||||
meta = camera_meta.get(cam_id, {})
|
||||
rms = meta.get("rms_px")
|
||||
nmk = meta.get("num_markers")
|
||||
rms_s = f"{rms:7.2f}" if rms is not None else " n/a"
|
||||
print(f"{cam_id:>5} {pos[0]:>9.1f} {pos[1]:>9.1f} {pos[2]:>9.1f} "
|
||||
f"{rms_s} {str(nmk):>4}")
|
||||
|
||||
# Marker-Tabelle
|
||||
print()
|
||||
hdr = (f"{'id':>5} {'set':<12} {'cams':>4} {'x':>8} {'y':>8} {'z':>8} "
|
||||
f"{'nx':>7} {'ny':>7} {'nz':>7} {'dxy':>7}")
|
||||
print(hdr)
|
||||
print("-" * len(hdr))
|
||||
for row in rows:
|
||||
dxy_s = f"{row['dxy']:7.2f}" if row['dxy'] != "" else " -"
|
||||
print(
|
||||
f"{row['id']:>5} {row['set']:<12} {row['SeenByCount']:>4} "
|
||||
f"{row['x']:>8.1f} {row['y']:>8.1f} {row['z']:>8.1f} "
|
||||
f"{row['nx']:>7.4f} {row['ny']:>7.4f} {row['nz']:>7.4f} {dxy_s}"
|
||||
)
|
||||
|
||||
# A0-Abgleich-Statistik (planarer Fehler gegen robot.json)
|
||||
dxys = np.array([row["dxy"] for row in rows if row["dxy"] != ""], dtype=float)
|
||||
if dxys.size:
|
||||
print(f"\nA0 dxy (Welt-Abgleich, mm): n={dxys.size} "
|
||||
f"mean={dxys.mean():.2f} median={np.median(dxys):.2f} "
|
||||
f"max={dxys.max():.2f}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
2956
test/temp/cam0_hires_1781074183695_aruco_detection.json
Normal file
2956
test/temp/cam0_hires_1781074183695_aruco_detection.json
Normal file
File diff suppressed because it is too large
Load Diff
719
test/temp/cam0_hires_1781074183695_camera_pose.json
Normal file
719
test/temp/cam0_hires_1781074183695_camera_pose.json
Normal file
@@ -0,0 +1,719 @@
|
||||
{
|
||||
"schema_version": "1.0",
|
||||
"created_utc": "2026-06-10T10:41:07Z",
|
||||
"source": {
|
||||
"detection_json": "C:\\Users\\kech\\SynologyDrive\\2026-AppServer-AppRobot\\appRobotRendering\\test\\temp\\cam0_hires_1781074183695_aruco_detection.json",
|
||||
"robot_json": "C:\\Users\\kech\\SynologyDrive\\2026-AppServer-AppRobot\\appRobotRendering\\data\\testPictures\\robot_1781069752019.json"
|
||||
},
|
||||
"camera": {
|
||||
"camera_id": "cam0",
|
||||
"camera_matrix": [
|
||||
[
|
||||
1429.6978759765625,
|
||||
0.0,
|
||||
633.3245239257812
|
||||
],
|
||||
[
|
||||
0.0,
|
||||
1414.5067138671875,
|
||||
468.4399108886719
|
||||
],
|
||||
[
|
||||
0.0,
|
||||
0.0,
|
||||
1.0
|
||||
]
|
||||
],
|
||||
"distortion_coefficients": [
|
||||
0.0862322673201561,
|
||||
0.14179007709026337,
|
||||
0.0014998731203377247,
|
||||
-0.004277258180081844,
|
||||
-0.7496029734611511
|
||||
]
|
||||
},
|
||||
"estimation": {
|
||||
"method": "single_camera_marker_center_lm",
|
||||
"description": "Rigid init from per-marker pose estimates, followed by LM on normalized marker-center reprojection residuals.",
|
||||
"marker_size_m": 0.025,
|
||||
"num_used_markers": 37,
|
||||
"used_marker_ids": [
|
||||
95,
|
||||
97,
|
||||
51,
|
||||
55,
|
||||
54,
|
||||
47,
|
||||
79,
|
||||
96,
|
||||
85,
|
||||
62,
|
||||
57,
|
||||
105,
|
||||
59,
|
||||
48,
|
||||
102,
|
||||
86,
|
||||
71,
|
||||
92,
|
||||
72,
|
||||
84,
|
||||
65,
|
||||
80,
|
||||
89,
|
||||
60,
|
||||
56,
|
||||
63,
|
||||
99,
|
||||
68,
|
||||
46,
|
||||
87,
|
||||
67,
|
||||
50,
|
||||
98,
|
||||
76,
|
||||
70,
|
||||
100,
|
||||
91
|
||||
],
|
||||
"history": {
|
||||
"iters": [
|
||||
0,
|
||||
1,
|
||||
2,
|
||||
3
|
||||
],
|
||||
"rms": [
|
||||
0.013977914197306877,
|
||||
0.0012063861436378766,
|
||||
0.00041790882674225575,
|
||||
0.000417864448222557
|
||||
],
|
||||
"lambda": [
|
||||
0.001,
|
||||
0.0005,
|
||||
0.00025,
|
||||
0.000125
|
||||
]
|
||||
},
|
||||
"residual_rms_px": 0.8488907668283678,
|
||||
"residual_median_px": 0.6015952243821542,
|
||||
"residual_max_px": 3.215993321685572,
|
||||
"sigma2_normalized": 1.900175232935359e-07
|
||||
},
|
||||
"camera_pose": {
|
||||
"world_to_camera": {
|
||||
"rotation_matrix": [
|
||||
[
|
||||
0.7153297066688538,
|
||||
-0.6744856238365173,
|
||||
0.18268170952796936
|
||||
],
|
||||
[
|
||||
-0.24956846237182617,
|
||||
-0.4907773733139038,
|
||||
-0.834777295589447
|
||||
],
|
||||
[
|
||||
0.6527013182640076,
|
||||
0.5515493750572205,
|
||||
-0.5193979740142822
|
||||
]
|
||||
],
|
||||
"translation_m": [
|
||||
-0.5062417984008789,
|
||||
0.09014879167079926,
|
||||
0.7660393714904785
|
||||
],
|
||||
"rvec_rad": [
|
||||
2.0691228499009884,
|
||||
-0.7015145339853286,
|
||||
0.6341981126084956
|
||||
]
|
||||
},
|
||||
"camera_in_world": {
|
||||
"position_m": [
|
||||
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BIN
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1850
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BIN
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3433
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test/temp/cam2_hires_1781074183695_debug.jpg
Normal file
BIN
test/temp/cam2_hires_1781074183695_debug.jpg
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test/temp/detections.csv
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test/temp/detections.csv
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|
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id,set,SeenByCount,x,y,z,nx,ny,nz,dxy
|
||||
cam0,CAMERA,,-115.37,-719.72,565.61,,,,
|
||||
cam1,CAMERA,,318.95,-523.93,853.64,,,,
|
||||
cam2,CAMERA,,-272.89,256.27,845.84,,,,
|
||||
0,?,2,513.41,-99.44,-19.39,-0.5015,-0.865,0.0182,
|
||||
46,A0,2,565.64,209.9,-55.56,0.0354,0.015,0.9993,37.88
|
||||
47,A0,3,362.8,-287.49,-65.76,-0.333,-0.3131,0.8894,18.59
|
||||
48,A0,2,761.75,-329.77,-88.34,-0.6704,0.4149,0.6152,73.62
|
||||
49,A0,1,1092.66,151.29,-83.59,-0.0347,-0.025,0.9991,86.95
|
||||
50,A0,2,630.74,265.32,-79.87,0.0073,-0.0024,1.0,78.39
|
||||
51,A0,3,176.56,-163.97,-69.44,-0.26,0.2559,0.9311,11.94
|
||||
52,A0,2,96.93,219.89,-55.7,-0.0341,-0.0377,0.9987,11.46
|
||||
53,A0,1,518.69,210.86,-64.22,0.0166,0.0014,0.9999,32.47
|
||||
54,A0,3,357.23,-330.04,-55.94,-0.2949,0.3095,0.904,14.97
|
||||
55,A0,3,296.01,-261.27,-57.66,-0.291,0.0608,0.9548,12.36
|
||||
56,A0,2,538.59,201.55,-67.84,-0.0012,0.0013,1.0,51.71
|
||||
57,A0,3,635.81,-362.16,-68.53,0.0282,-0.001,0.9996,33.01
|
||||
58,A0,2,49.92,-219.72,-67.42,0.0418,-0.0158,0.999,1.62
|
||||
59,A0,3,664.52,-276.95,-69.92,-0.4034,-0.2722,0.8736,38.35
|
||||
60,A0,2,465.81,316.89,-63.04,-0.4284,-0.7766,0.462,45.64
|
||||
61,A0,1,-11.44,338.72,-61.53,0.0583,-0.0284,0.9979,11.35
|
||||
62,A0,3,423.81,-171.25,-62.26,-0.0275,-0.2428,0.9697,19.49
|
||||
63,A0,2,858.89,-229.54,-87.46,-0.0167,0.0026,0.9999,81.75
|
||||
64,A0,2,-21.74,-191.34,-56.41,-0.2806,0.4588,0.8431,3.14
|
||||
65,A0,2,876.99,-304.2,-81.63,0.0086,-0.0228,0.9997,73.92
|
||||
66,A0,2,221.89,-378.26,-70.96,-0.3787,0.5606,0.7364,19.32
|
||||
67,A0,2,570.28,307.19,-74.97,-0.665,-0.023,0.7465,61.98
|
||||
68,A0,2,615.28,185.13,-67.64,0.0036,0.0103,0.9999,44.0
|
||||
69,A0,2,7.51,-289.23,-71.43,0.0655,0.0143,0.9977,8.02
|
||||
70,A0,2,646.35,344.94,-66.82,0.013,0.0124,0.9998,63.0
|
||||
71,A0,2,801.68,-284.13,-67.44,-0.0049,0.0036,1.0,51.93
|
||||
72,A0,2,470.53,219.63,-59.99,-0.8891,-0.3928,-0.2349,38.9
|
||||
73,A0,1,227.77,334.47,-38.57,0.0887,-0.003,0.9961,6.19
|
||||
74,A0,2,93.61,158.28,-59.95,-0.4017,0.1293,0.9066,13.78
|
||||
75,A0,2,-31.35,211.98,-57.21,-0.1993,-0.6229,0.7565,18.29
|
||||
76,A0,2,725.6,203.41,-58.89,-0.5971,-0.6684,0.4436,54.51
|
||||
77,A0,2,14.87,208.14,-61.15,-0.2433,-0.6323,0.7355,16.9
|
||||
79,A0,3,324.61,-146.67,-56.54,-0.0051,-0.0055,1.0,17.5
|
||||
80,A0,1,920.78,-313.59,-61.98,0.0261,-0.0109,0.9996,61.4
|
||||
81,A0,2,134.74,179.65,-55.28,0.1542,-0.6375,0.7549,10.94
|
||||
82,A0,1,235.39,299.34,-56.31,0.0119,-0.0171,0.9998,16.36
|
||||
83,A0,1,60.54,343.24,-73.55,-0.0211,-0.0083,0.9997,16.87
|
||||
84,A0,2,433.15,283.86,-57.97,0.0108,0.0308,0.9995,36.13
|
||||
85,A0,3,530.97,-312.83,-65.01,-0.5392,0.0418,0.8411,26.39
|
||||
86,A0,2,371.18,293.37,-37.99,0.0359,0.0184,0.9992,8.4
|
||||
87,A0,1,992.42,-224.08,-54.87,0.0164,-0.0161,0.9997,53.39
|
||||
89,A0,1,1087.35,-337.82,-77.4,-0.8097,-0.3076,-0.4998,104.15
|
||||
90,A0,1,716.28,322.0,-98.36,-0.9961,-0.0881,-0.0008,73.33
|
||||
91,A0,2,797.63,384.71,-85.91,-0.6357,-0.6612,0.3984,93.42
|
||||
92,A0,3,689.76,-175.44,-72.48,-0.4179,0.1772,0.8911,45.65
|
||||
94,A0,1,912.67,170.82,-55.05,0.0401,-0.0161,0.9991,37.08
|
||||
95,A0,3,196.36,-271.55,-63.02,-0.263,-0.3771,0.8881,10.62
|
||||
96,A0,3,386.86,-188.18,-58.96,-0.0153,-0.2337,0.9722,17.17
|
||||
97,A0,3,317.16,-361.37,-54.79,-0.242,-0.4685,0.8497,12.92
|
||||
98,A0,2,648.49,382.72,-96.14,-0.001,0.016,0.9999,99.69
|
||||
99,A0,1,1032.86,-294.32,-67.94,-0.7854,-0.2944,-0.5445,78.57
|
||||
100,A0,2,848.99,192.39,-61.29,-0.6582,-0.6214,0.4251,49.94
|
||||
101,A0,1,131.96,300.1,-59.87,0.0067,0.0277,0.9996,14.34
|
||||
102,A0,3,683.89,-213.5,-68.38,-0.2212,-0.1903,0.9565,35.49
|
||||
103,A0,2,111.85,-193.49,-59.79,0.0184,0.0312,0.9993,8.43
|
||||
105,A0,3,553.96,-263.47,-68.08,-0.4035,-0.285,0.8695,29.26
|
||||
201,?,1,897.13,61.75,90.23,-0.9978,0.0489,0.0451,
|
||||
208,?,3,683.3,-76.41,-55.32,-0.3861,-0.3324,0.8605,
|
||||
210,?,2,153.21,-2.51,-63.41,-0.3954,0.267,0.8788,
|
||||
211,?,3,359.71,3.01,-41.85,0.0415,0.0337,0.9986,
|
||||
214,?,3,595.34,16.16,-69.24,-0.9274,-0.1985,0.3172,
|
||||
215,?,3,353.19,-91.68,-33.15,-0.2708,-0.4026,0.8744,
|
||||
217,?,1,764.54,-10.41,-25.65,0.106,0.004,0.9944,
|
||||
218,?,1,1121.04,-225.1,28.11,-0.7647,-0.6357,0.1053,
|
||||
219,?,1,1127.16,-337.07,20.54,-0.9004,-0.4335,0.038,
|
||||
|
Reference in New Issue
Block a user