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@@ -211,7 +211,7 @@ def compute_connections(pafs, all_peaks, img_len, cfg): |
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cand_a = all_peaks[all_peaks[:, 0] == limb_point[0]][:, 1:] |
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cand_b = all_peaks[all_peaks[:, 0] == limb_point[1]][:, 1:] |
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if cand_a and cand_b: |
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if cand_a.shape[0] > 0 and cand_b.shape[0] > 0: |
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candidate_connections = compute_candidate_connections(paf, cand_a, cand_b, img_len, cfg) |
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connections = np.zeros((0, 3)) |
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@@ -346,7 +346,7 @@ def detect(img, network): |
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cv2.imwrite(save_path, heatmaps[i]*255) |
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all_peaks = compute_peaks_from_heatmaps(heatmaps) |
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if not all_peaks: |
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if all_peaks.shape[0] == 0: |
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return np.empty((0, len(JointType), 3)), np.empty(0) |
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all_connections = compute_connections(pafs, all_peaks, map_w, params) |
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subsets = grouping_key_points(all_connections, all_peaks, params) |
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@@ -359,7 +359,7 @@ def detect(img, network): |
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def draw_person_pose(orig_img, poses): |
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orig_img = cv2.cvtColor(orig_img, cv2.COLOR_BGR2RGB) |
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if not poses: |
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if poses.shape[0] == 0: |
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return orig_img |
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limb_colors = [ |
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@@ -426,7 +426,7 @@ def _eval(): |
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img_id = int((img_id.asnumpy())[0]) |
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poses, scores = detect(img, network) |
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if poses: |
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if poses.shape[0] > 0: |
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#print("got poses") |
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for index, pose in enumerate(poses): |
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data = dict() |
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