revise model.eval()

demo/key_point_detection/openpose_body/predict.py

@@ -5,5 +5,4 @@ if __name__ == "__main__":
 
     paddle.disable_static()
     model = hub.Module(name='openpose_body_estimation')
-    model.eval()
     out1, out2 = model.predict("demo.jpg")

demo/key_point_detection/openpose_hands/predict.py

@@ -5,5 +5,4 @@ if __name__ == "__main__":
 
     paddle.disable_static()
     model = hub.Module(name='openpose_hands_estimation')
-    model.eval()
     all_hand_peaks = model.predict("demo.jpg")

hub_module/modules/image/keypoint_detection/openpose_body_estimation/module.py

@@ -180,6 +180,7 @@ class BodyPoseModel(nn.Layer):
         return out6_1, out6_2
 
     def predict(self, img_path: str, save_path: str = "result"):
+        self.eval()
         orgImg = cv2.imread(img_path)
         data, imageToTest_padded, pad = self.transform(orgImg)
         Mconv7_stage6_L1, Mconv7_stage6_L2 = self.forward(paddle.to_tensor(data))

hub_module/modules/image/keypoint_detection/openpose_hands_estimation/module.py

@@ -170,6 +170,7 @@ class HandPoseModel(nn.Layer):
         return np.array(all_peaks)
 
     def predict(self, img_path: str, save_path: str = 'result', scale: list = [0.5, 1.0, 1.5, 2.0]):
+        self.eval()
         self.body_model = hub.Module(name='openpose_body_estimation')
         self.body_model.eval()
         org_img = cv2.imread(img_path)