Update objdetect benchmark formatting#7
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asmorkalov merged 20 commits intoopencv:developfrom Oct 18, 2023
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AleksandrPanov
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Sep 28, 2023
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| self.col_offset:self.col_offset + image.shape[1]] = image | ||
| self.col_offset:self.col_offset + image.shape[1]] = image |
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tab refactoring
AleksandrPanov
commented
Sep 28, 2023
AleksandrPanov
commented
Sep 28, 2023
AleksandrPanov
commented
Sep 28, 2023
AleksandrPanov
commented
Sep 28, 2023
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| def check_aruco(synthetic_aruco, marker_corners, marker_ids, accuracy, type_dist): | ||
| gold = {} | ||
| gold_corners, gold_ids = synthetic_aruco.aruco_corners.reshape(-1, 4, 2), \ | ||
| synthetic_aruco.aruco_ids | ||
| for marker_id, marker in zip(gold_ids, gold_corners): | ||
| gold[int(marker_id)] = marker | ||
| dist = 0. | ||
| detected_count = 0 | ||
| total_count = len(gold_ids) | ||
| detected = {} | ||
| if len(marker_ids) > 0: | ||
| for marker_id, marker in zip(marker_ids, marker_corners): | ||
| detected[int(marker_id)] = marker.reshape(4, 2) | ||
| for gold_id in gold_ids: | ||
| gold_corner = gold_corners[int(gold_id)] | ||
| if int(gold_id) in detected: | ||
| corner = detected[int(gold_id)] | ||
| loc_dist = get_norm(gold_corner, corner, type_dist) | ||
| if loc_dist < accuracy: | ||
| dist += loc_dist | ||
| detected_count += 1 | ||
| return detected_count, total_count, dist |
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move to @staticmethod
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asmorkalov
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Oct 16, 2023
| plt.rcParams["figure.subplot.right"] = 0.99 | ||
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| def print_category_frame(obj_type, category, statistics, accuracy, path): |
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bad function name. Not clear what it does.
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renamed to get_and_print_category_statistic
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| contourpy==1.1.1 | ||
| cycler==0.12.0 | ||
| fonttools==4.43.0 | ||
| iteration-utilities==0.11.0 | ||
| kiwisolver==1.4.5 | ||
| matplotlib==3.8.0 | ||
| matplotlib-venn==0.11.9 | ||
| numpy==1.24.2 | ||
| opencv-python==4.8.1.78 | ||
| packaging==23.2 | ||
| pandas==2.1.1 | ||
| Pillow==9.4.0 | ||
| pyparsing==3.1.1 | ||
| python-dateutil==2.8.2 | ||
| pytz==2023.3.post1 | ||
| scipy==1.11.3 | ||
| six==1.16.0 | ||
| tzdata==2023.3 |
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The dependencies are to strict and some of them redundant. I propose to exclude numpy and opencv-python as the test version may differ from the requirements.
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Here is an example of the program output:
