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| import math | |
| import numpy as np | |
| import matplotlib | |
| import cv2 | |
| eps = 0.01 | |
| def alpha_blend_color(color, alpha): | |
| """blend color according to point conf | |
| """ | |
| return [int(c * alpha) for c in color] | |
| def draw_bodypose(canvas, candidate, subset, score): | |
| H, W, C = canvas.shape | |
| candidate = np.array(candidate) | |
| subset = np.array(subset) | |
| stickwidth = 4 | |
| limbSeq = [[2, 3], [2, 6], [3, 4], [4, 5], [6, 7], [7, 8], [2, 9], [9, 10], \ | |
| [10, 11], [2, 12], [12, 13], [13, 14], [2, 1], [1, 15], [15, 17], \ | |
| [1, 16], [16, 18], [3, 17], [6, 18]] | |
| colors = [[255, 0, 0], [255, 85, 0], [255, 170, 0], [255, 255, 0], [170, 255, 0], [85, 255, 0], [0, 255, 0], \ | |
| [0, 255, 85], [0, 255, 170], [0, 255, 255], [0, 170, 255], [0, 85, 255], [0, 0, 255], [85, 0, 255], \ | |
| [170, 0, 255], [255, 0, 255], [255, 0, 170], [255, 0, 85]] | |
| for i in range(17): | |
| for n in range(len(subset)): | |
| index = subset[n][np.array(limbSeq[i]) - 1] | |
| conf = score[n][np.array(limbSeq[i]) - 1] | |
| if conf[0] < 0.3 or conf[1] < 0.3: | |
| continue | |
| Y = candidate[index.astype(int), 0] * float(W) | |
| X = candidate[index.astype(int), 1] * float(H) | |
| mX = np.mean(X) | |
| mY = np.mean(Y) | |
| length = ((X[0] - X[1]) ** 2 + (Y[0] - Y[1]) ** 2) ** 0.5 | |
| angle = math.degrees(math.atan2(X[0] - X[1], Y[0] - Y[1])) | |
| polygon = cv2.ellipse2Poly((int(mY), int(mX)), (int(length / 2), stickwidth), int(angle), 0, 360, 1) | |
| cv2.fillConvexPoly(canvas, polygon, alpha_blend_color(colors[i], conf[0] * conf[1])) | |
| canvas = (canvas * 0.6).astype(np.uint8) | |
| for i in range(18): | |
| for n in range(len(subset)): | |
| index = int(subset[n][i]) | |
| if index == -1: | |
| continue | |
| x, y = candidate[index][0:2] | |
| conf = score[n][i] | |
| x = int(x * W) | |
| y = int(y * H) | |
| cv2.circle(canvas, (int(x), int(y)), 4, alpha_blend_color(colors[i], conf), thickness=-1) | |
| return canvas | |
| def draw_handpose(canvas, all_hand_peaks, all_hand_scores): | |
| H, W, C = canvas.shape | |
| edges = [[0, 1], [1, 2], [2, 3], [3, 4], [0, 5], [5, 6], [6, 7], [7, 8], [0, 9], [9, 10], \ | |
| [10, 11], [11, 12], [0, 13], [13, 14], [14, 15], [15, 16], [0, 17], [17, 18], [18, 19], [19, 20]] | |
| for peaks, scores in zip(all_hand_peaks, all_hand_scores): | |
| for ie, e in enumerate(edges): | |
| x1, y1 = peaks[e[0]] | |
| x2, y2 = peaks[e[1]] | |
| x1 = int(x1 * W) | |
| y1 = int(y1 * H) | |
| x2 = int(x2 * W) | |
| y2 = int(y2 * H) | |
| score = int(scores[e[0]] * scores[e[1]] * 255) | |
| if x1 > eps and y1 > eps and x2 > eps and y2 > eps: | |
| cv2.line(canvas, (x1, y1), (x2, y2), | |
| matplotlib.colors.hsv_to_rgb([ie / float(len(edges)), 1.0, 1.0]) * score, thickness=2) | |
| for i, keyponit in enumerate(peaks): | |
| x, y = keyponit | |
| x = int(x * W) | |
| y = int(y * H) | |
| score = int(scores[i] * 255) | |
| if x > eps and y > eps: | |
| cv2.circle(canvas, (x, y), 4, (0, 0, score), thickness=-1) | |
| return canvas | |
| def draw_facepose(canvas, all_lmks, all_scores): | |
| H, W, C = canvas.shape | |
| for lmks, scores in zip(all_lmks, all_scores): | |
| for lmk, score in zip(lmks, scores): | |
| x, y = lmk | |
| x = int(x * W) | |
| y = int(y * H) | |
| conf = int(score * 255) | |
| if x > eps and y > eps: | |
| cv2.circle(canvas, (x, y), 3, (conf, conf, conf), thickness=-1) | |
| return canvas | |
| def draw_pose(pose, H, W, ref_w=2160): | |
| """vis dwpose outputs | |
| Args: | |
| pose (List): DWposeDetector outputs in dwpose_detector.py | |
| H (int): height | |
| W (int): width | |
| ref_w (int, optional) Defaults to 2160. | |
| Returns: | |
| np.ndarray: image pixel value in RGB mode | |
| """ | |
| bodies = pose['bodies'] | |
| faces = pose['faces'] | |
| hands = pose['hands'] | |
| candidate = bodies['candidate'] | |
| subset = bodies['subset'] | |
| sz = min(H, W) | |
| sr = (ref_w / sz) if sz != ref_w else 1 | |
| ########################################## create zero canvas ################################################## | |
| canvas = np.zeros(shape=(int(H*sr), int(W*sr), 3), dtype=np.uint8) | |
| ########################################### draw body pose ##################################################### | |
| canvas = draw_bodypose(canvas, candidate, subset, score=bodies['score']) | |
| ########################################### draw hand pose ##################################################### | |
| canvas = draw_handpose(canvas, hands, pose['hands_score']) | |
| ########################################### draw face pose ##################################################### | |
| canvas = draw_facepose(canvas, faces, pose['faces_score']) | |
| return cv2.cvtColor(cv2.resize(canvas, (W, H)), cv2.COLOR_BGR2RGB).transpose(2, 0, 1) | |