output pose coords as list

libs/easy_dwpose/dwpose.py

@@ -26,7 +26,7 @@ class DWposeDetector:
         candidates[..., 1] /= float(height)
 
         bodies = candidates[:, :18].copy()
-        bodies = bodies.reshape(num_candidates * 18, locs)
+        bodies_flat = bodies.reshape(num_candidates * 18, locs)
 
         body_scores = scores[:, :18]
         for i in range(len(body_scores)):
@@ -43,12 +43,14 @@ class DWposeDetector:
         hands_scores = np.vstack([scores[:, 92:113], scores[:, 113:]])
 
         pose = dict(
-            bodies=bodies,
+            bodies=bodies_flat,
+            bodies_multi=bodies,
             body_scores=body_scores,
             hands=hands,
             hands_scores=hands_scores,
             faces=faces,
             faces_scores=faces_scores,
+            num_candidates=num_candidates,
         )
 
         return pose

main.py

@@ -314,7 +314,12 @@ def prepare_inputs_inference(in_img, in_vid, fps, dwpose, rembg_session, bg_remo
         #print(tpose_coords)
         coords = {}
         for k in tpose_coords:
-            coords[k] = tpose_coords[k].tolist()
+            if k == 'bodies_multi':
+                coords['bodies'] = tpose_coords[k].tolist()
+            elif k in ['hands']:
+                coords[k] = tpose_coords[k].tolist()
+            elif k in ['num_candidates']:
+                coords[k] = tpose_coords[k]
         #print(coords)
         target_poses.append(tpose)
         target_poses_coords.append(json.dumps(coords))