- revised calibration
- cleaned up unused parameter - use CALIB_RATIONAL_MODEL for better wide angle matching
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@@ -37,22 +37,22 @@ class Calibration:
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pass
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def save(self, filename: str):
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mtx, dist = self.get()
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np.savez(f"{filename}", mtx=mtx, dist=dist)
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calib = {'mtx': mtx.tolist(), 'dist': dist.tolist()}
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print(f"Saved {filename} successfully!")
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if self.mtx is not None and self.dist is not None:
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np.savez(f"{filename}", mtx=self.mtx, dist=self.dist)
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print(f"Saved {filename} successfully!")
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def process(self, image: np.ndarray, thresh=3.0, r_vecs=None, t_vecs=None, flags=0):
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success = False
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def process(self, image: np.ndarray, thresh=3.0):
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criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 3000, 0.001)
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error = None
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no = len(self.obj_points_list)
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ni = len(self.img_points_list)
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if no == ni and no > 0:
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ret, mtx, dist, r_vecs, t_vecs = cv.calibrateCamera(self.obj_points_list, self.img_points_list, image.shape, self.mtx, self.dist,
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rvecs=r_vecs, tvecs=t_vecs, flags=flags)
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rvecs=None, tvecs=None, flags=cv.CALIB_RATIONAL_MODEL, criteria=criteria)
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if ret < thresh:
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success = True
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error = ret
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self.mtx = mtx
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self.dist = dist
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return success
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return error
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@@ -186,9 +186,12 @@ class Detector(abc.ABC):
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print(f"{det}: Points matching success")
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elif k == ord('c'):
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gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
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if self.calibration.process(gray, thresh=3*len(self.detector)):
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print(f"{self.camera_name}: Camera calibration success")
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calib_err = self.calibration.process(gray, thresh=3*len(self.detector))
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if calib_err is not None:
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print(f"{self.camera_name}: Calibration success: Reprojection error={calib_err}")
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self.calibration.save(f"{RESULTS_FOLDER}/{self.camera_name}_cal.npz")
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else:
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print(f"{self.camera_name}: Calibration failed")
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elif k == ord('x'):
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self.calibration.calibration_clear()
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elif k == ord('f'):
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