Special cases of optimization 0. 0

easy_dwpose/draw/controlnext.py

@@ -55,8 +55,11 @@ def draw_bodypose(canvas, candidate, subset, score, transparent=False, hide_tors
             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)
+            coords = candidate[index.astype(int)]
+            if np.any(coords <= eps):
+                continue
+            Y = coords[:, 0] * float(W)
+            X = coords[:, 1] * float(H)
             mX = np.mean(X)
             mY = np.mean(Y)
             length = ((X[0] - X[1]) ** 2 + (Y[0] - Y[1]) ** 2) ** 0.5
@@ -86,6 +89,8 @@ def draw_bodypose(canvas, candidate, subset, score, transparent=False, hide_tors
                 continue
             x, y = candidate[index][0:2]
             conf = score[n][i]
+            if x <= eps or y <= eps:
+                continue
             x = int(x * W)
             y = int(y * H)
             if transparent:
@@ -254,4 +259,4 @@ def process_pose_data(pose_data: Dict[str, Any], height: int, width: int) -> Dic
     processed_data['faces'] = adjusted_faces
     processed_data['faces_score'] = pose_data['faces_scores']
     
-    return processed_data
+    return processed_data

easy_dwpose/draw/openpose.py

@@ -77,8 +77,12 @@ def draw_bodypose(canvas, candidate, subset, score=None, conf_threshold=0.3):
                 if conf[0] < conf_threshold or conf[1] < conf_threshold:
                     continue
 
-            Y = candidate[index.astype(int), 0] * float(W)
-            X = candidate[index.astype(int), 1] * float(H)
+            coords = candidate[index.astype(int)]
+            if np.any(coords <= eps):
+                continue
+
+            Y = coords[:, 0] * float(W)
+            X = coords[:, 1] * float(H)
             mX = np.mean(X)
             mY = np.mean(Y)
             length = ((X[0] - X[1]) ** 2 + (Y[0] - Y[1]) ** 2) ** 0.5