fix issues for pytorch<1.9.0.

.gitignore

@@ -123,4 +123,6 @@ venv.bak/
 
 # project
 results/
+dlib/
 *_old*
+

facelib/detection/yolov5face/face_detector.py

@@ -17,6 +17,9 @@ from facelib.detection.yolov5face.utils.general import (
     scale_coords_landmarks,
 )
 
+IS_HIGH_VERSION = tuple(map(int, torch.__version__.split('+')[0].split('.'))) >= (1, 9, 0)
+
+
 def isListempty(inList):
     if isinstance(inList, list): # Is a list
         return all(map(isListempty, inList))
@@ -116,8 +119,14 @@ class YoloDetector:
         origimgs = copy.deepcopy(images)
 
         images = self._preprocess(images)
-        with torch.inference_mode():  # change this with torch.no_grad() for pytorch <1.8 compatibility
-            pred = self.detector(images)[0]
+        
+        if IS_HIGH_VERSION:
+            with torch.inference_mode():  # for pytorch>=1.9 
+                pred = self.detector(images)[0]
+        else:
+            with torch.no_grad():  # for pytorch<1.9
+                pred = self.detector(images)[0]
+
         bboxes, points = self._postprocess(images, origimgs, pred, conf_thres, iou_thres)
 
         # return bboxes, points

facelib/detection/yolov5face/models/yolo.py

@@ -87,7 +87,8 @@ class Detect(nn.Module):
 
     @staticmethod
     def _make_grid(nx=20, ny=20):
-        yv, xv = torch.meshgrid([torch.arange(ny), torch.arange(nx)], indexing="ij")
+        # yv, xv = torch.meshgrid([torch.arange(ny), torch.arange(nx)], indexing="ij") # for pytorch>=1.10
+        yv, xv = torch.meshgrid([torch.arange(ny), torch.arange(nx)])
         return torch.stack((xv, yv), 2).view((1, 1, ny, nx, 2)).float()
 
 

facelib/utils/face_restoration_helper.py

@@ -69,7 +69,7 @@ class FaceRestoreHelper(object):
             self.face_template = np.array([[192, 240], [319, 240], [257, 371]])
         else:
             # standard 5 landmarks for FFHQ faces with 512 x 512 
-            # # xintao
+            # facexlib
             self.face_template = np.array([[192.98138, 239.94708], [318.90277, 240.1936], [256.63416, 314.01935],
                                            [201.26117, 371.41043], [313.08905, 371.15118]])
 

inference_codeformer.py

@@ -91,8 +91,6 @@ if __name__ == '__main__':
         face_helper.clean_all()
 
         img_name = os.path.basename(img_path)
-        # if not '04' in img_name:
-        #     continue 
         print(f'Processing: {img_name}')
         basename, ext = os.path.splitext(img_name)
         img = cv2.imread(img_path, cv2.IMREAD_COLOR)