Spaces:
Runtime error
Runtime error
File size: 5,896 Bytes
b9cc655 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 |
import numpy as np
def get_width(mask, keypoint_y):
pred_np = mask.numpy()
# Find the index of the first occurrence of the mask label
first_index = np.argmax(pred_np[keypoint_y,:] > 0)
# Find the index of the last occurrence of the mask label
last_index = len(pred_np[keypoint_y,:]) - np.argmax(np.flip(pred_np[keypoint_y,:]) > 0) - 1
return last_index-first_index
def calculate_all_measures(front_keypoints, side_keypoints, front_seg_mask, side_rcnn_mask):
results_dict = {}
# calculate the body length
# pick the longer from the two ankle keypoints on y coordinate
side_body_length = side_keypoints[15][1] if side_keypoints[15][1] > side_keypoints[16][1] else side_keypoints[16][1]
# 5: 'left_shoulder'
left_shoulder_y = round(front_keypoints[5][1])
# print("shoulder width", get_width(front_seg_mask, left_shoulder_y))
results_dict['shoulder_width'] = get_width(front_seg_mask, left_shoulder_y)
# remove left-arm mask
front_seg_mask[front_seg_mask == 14] = 0
# remove right-arm mask
front_seg_mask[front_seg_mask == 15] = 0
# 11: 'left_hip'
left_hip_y = round(front_keypoints[11][1])
# print("hip width", get_width(front_seg_mask, left_hip_y))
results_dict['hip_width'] = get_width(front_seg_mask, left_hip_y)
# calculate shoulder_to_hip distance
shoulder_to_hip_distance = front_keypoints[11][1] - front_keypoints[5][1]
# print("Shoulder to hip distance:", shoulder_to_hip_distance)
results_dict['shoulder_to_hip_distance'] = shoulder_to_hip_distance
# calculate hip_to_ankle distance
hip_to_ankle_distance = front_keypoints[16][1] - front_keypoints[12][1]
# print("Hip to ankle distance:", hip_to_ankle_distance)
results_dict['hip_to_ankle_distance'] = hip_to_ankle_distance
# calculate torso_to_leg proportions
torso_to_leg_proportions = shoulder_to_hip_distance / hip_to_ankle_distance
# print("Torso to leg proportions:", torso_to_leg_proportions)
results_dict['torso_to_leg_ratio'] = torso_to_leg_proportions
# waist
# assuming waistline is x % higher from hips
# hip_y axis - (40 % of shoulder to hip distance)
waist_y = round(front_keypoints[11][1] - (shoulder_to_hip_distance * 0.40))
# print("waist width", get_width(front_seg_mask, waist_y))
results_dict['waist_width'] = get_width(front_seg_mask, waist_y)
# Calculate bounding box for thigh
# right_knee = side_keypoints[side_keypoint_names.index("right_knee")]
# right_hip = side_keypoints[side_keypoint_names.index("right_hip")]
# # Calculate bounding box for torso
# right_shoulder = side_keypoints[side_keypoint_names.index("right_shoulder")]
# # Replace keypoints, keypoint_names, combined_mask, and original_image with your actual data
# thigh_bbox = calculate_bbox(side_original_image, right_knee, right_hip)
# torso_bbox = calculate_bbox(side_original_image, right_hip, right_shoulder)
# # Calculate midpoint coordinates
# torso_midpoint = [0, (right_hip[1] + right_shoulder[1]) / 2]
# lower_torso_bbox = calculate_bbox(side_original_image, right_hip, torso_midpoint)
# upper_torso_bbox = calculate_bbox(side_original_image, torso_midpoint, right_shoulder)
# # Replace keypoints, keypoint_names, combined_mask, and original_image with your actual data
# thigh_area = get_volume_result(side_rcnn_mask, side_original_image, thigh_bbox[1], thigh_bbox[0], thigh_bbox[3], thigh_bbox[2]) # Thigh volume
# torso_area = get_volume_result(side_rcnn_mask, side_original_image, torso_bbox[1], torso_bbox[0], torso_bbox[3], torso_bbox[2]) # Torso volume
# lower_torso_area = get_volume_result(side_rcnn_mask, side_original_image, lower_torso_bbox[1], lower_torso_bbox[0], lower_torso_bbox[3], lower_torso_bbox[2]) # Lower torso volume
# upper_torso_area = get_volume_result(side_rcnn_mask, side_original_image, upper_torso_bbox[1], upper_torso_bbox[0], upper_torso_bbox[3], upper_torso_bbox[2]) # Upper torso volume
# full_side_body_area = (side_rcnn_mask > 0).sum()
# # print(f"Thigh area: {thigh_area}")
# # print(f"Torso area: {torso_area}")
# # print(f"Lower torso area: {lower_torso_area}")
# # print(f"Upper torso area: {upper_torso_area}")
# results_dict['thigh_area'] = thigh_area
# results_dict['torso_area'] = torso_area
# results_dict['lower_torso_area'] = lower_torso_area
# results_dict['upper_torso_area'] = upper_torso_area
# results_dict['full_side_body_area'] = full_side_body_area
# # calculate ratios
# results_dict['thigh_normalised'] = thigh_area / side_body_length
# results_dict['torso_normalised'] = torso_area / side_body_length
# results_dict['thigh_to_torso_ratio_normalised'] = results_dict['thigh_normalised'] / results_dict['torso_normalised']
# results_dict['thigh_to_torso_ratio'] = thigh_area / torso_area
# results_dict['upper_torso_normalised'] = upper_torso_area / side_body_length
# results_dict['lower_torso_normalised'] = lower_torso_area / side_body_length
# results_dict['upper_to_lower_torso_normalised_ratio'] = results_dict['upper_torso_normalised'] / results_dict['lower_torso_normalised']
# results_dict['upper_to_lower_torso_ratio'] = upper_torso_area / lower_torso_area
# results_dict['shoulder_to_hip_ratio'] = results_dict['shoulder_width'] / results_dict['hip_width']
# results_dict['shoulder_to_waist_ratio'] = results_dict['shoulder_width'] / results_dict['waist_width']
# results_dict['waist_to_hip_ratio'] = results_dict['waist_width'] / results_dict['hip_width']
# results_dict['thigh_to_body_ratio'] = thigh_area / full_side_body_area
# results_dict['upper_torso_to_body_ratio'] = upper_torso_area / full_side_body_area
# results_dict['upper_torso_to_body_ratio'] = upper_torso_area / full_side_body_area
return dict
|