fix some bugs for training.

basicsr/data/ffhq_blind_dataset.py

@@ -232,7 +232,7 @@ class FFHQBlindDataset(data.Dataset):
             # jpeg
             if self.jpeg_range is not None:
                 jpeg_p = np.random.uniform(self.jpeg_range[0], self.jpeg_range[1])
-                encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), jpeg_p]
+                encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), int(jpeg_p)]
                 _, encimg = cv2.imencode('.jpg', img_in * 255., encode_param)
                 img_in = np.float32(cv2.imdecode(encimg, 1)) / 255.
 

basicsr/data/ffhq_blind_joint_dataset.py

@@ -224,7 +224,7 @@ class FFHQBlindJointDataset(data.Dataset):
             # jpeg
             if self.jpeg_range is not None:
                 jpeg_p = np.random.uniform(self.jpeg_range[0], self.jpeg_range[1])
-                encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), jpeg_p]
+                encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), int(jpeg_p)]
                 _, encimg = cv2.imencode('.jpg', img_in * 255., encode_param)
                 img_in = np.float32(cv2.imdecode(encimg, 1)) / 255.
 
@@ -267,7 +267,7 @@ class FFHQBlindJointDataset(data.Dataset):
             # jpeg
             if self.jpeg_range_large is not None:
                 jpeg_p = np.random.uniform(self.jpeg_range_large[0], self.jpeg_range_large[1])
-                encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), jpeg_p]
+                encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), int(jpeg_p)]
                 _, encimg = cv2.imencode('.jpg', img_in_large * 255., encode_param)
                 img_in_large = np.float32(cv2.imdecode(encimg, 1)) / 255.
 

options/CodeFormer_stage3.yml

@@ -85,7 +85,7 @@ network_d:
 path:
   pretrain_network_g: './experiments/pretrained_models/CodeFormer_stage2/net_g_latest.pth' # pretrained G model in StageII 
   param_key_g: params_ema
-  strict_load_g: true
+  strict_load_g: false
   pretrain_network_d: './experiments/pretrained_models/CodeFormer_stage2/net_d_latest.pth' # pretrained D model in StageII
   resume_state: ~