upload

src/pose_decode.py

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+import cv2
+import numpy as np
+import math
+import os, sys
+sys.path.append('../..')
+
+heatmap_width = 92
+heatmap_height = 92
+
+"""
+14 joints:
+0-right shoulder, 1-right elbow, 2-right wrist, 3-left shoulder, 4-left elbow, 5-left wrist, 
+6-right hip, 7-right knee, 8-right ankle, 9-left hip, 10-left knee, 11-left ankle, 
+12-top of the head and 13-neck
+"""
+
+JOINT_LIMB = [[0, 1], [1, 2], [3, 4], [4, 5], [6, 7], [7, 8], [9, 10], [10, 11], [12, 13], [13, 0], [13, 3], [13, 6], [13, 9]]
+COLOR = [[0, 255, 255], [0, 255, 255],[0, 255, 255],[0, 255, 255],[0, 255, 0],[0, 255, 0],[0, 255, 0],[0, 255, 0], [0, 0, 255], [255, 0, 0],[255, 0, 0],[255, 0, 0], [255, 0, 0]]
+
+def decode_pose(heatmaps, scale, image_original):
+
+    #obtain joint list from heatmap
+    joint_list = [peak_index_to_coords(heatmap)*scale for heatmap in heatmaps]
+
+    #plot the pose on original image
+    canvas = image_original
+    for idx, limb in enumerate(JOINT_LIMB):
+        joint_from, joint_to = joint_list[limb[0]], joint_list[limb[1]]
+        canvas = cv2.line(canvas, tuple(joint_from.astype(int)), tuple(joint_to.astype(int)), color=COLOR[idx], thickness=4)
+    return canvas  
+
+
+def peak_index_to_coords(peak_index):
+    '''
+    @peak_index is the index of max value in flatten heatmap
+    This function convert it back to the coordinates of the original heatmap 
+    '''
+    peak_coords = np.unravel_index(int(peak_index),(heatmap_height, heatmap_width))
+    return np.flip(peak_coords)