Update face_enhancer.py

face_enhancer.py

@@ -34,9 +34,9 @@ def codeformer_runner(img, model):
 supported_enhancers = {
     "CodeFormer": ("./assets/pretrained_models/codeformer.onnx", codeformer_runner),
     "GFPGAN": ("./assets/pretrained_models/GFPGANv1.4.pth", gfpgan_runner),
-    "Real_Hatgan x4": ("./assets/pretrained_models/real_hatgan_x4.onnx", realhatgan_runner),
-    "Ultra_Sharp x4": ("./assets/pretrained_models/ultra_sharp_x4.onnx", ultrasharp_runner),
-    "RestoreFormer": ("./assets/pretrained_models/restoreformer_plus_plus.onnx", restoreformer_runner),
+    "REAL_HATGAN x4": ("./assets/pretrained_models/real_hatgan_x4.onnx", realhatgan_runner),
+    "ULTRA_SHARP x4": ("./assets/pretrained_models/ultra_sharp_x4.onnx", ultrasharp_runner),
+    "RESTOREFORMER PLUS PLUS": ("./assets/pretrained_models/restoreformer_plus_plus.onnx", restoreformer_runner),
     "REAL-ESRGAN 2x": ("./assets/pretrained_models/RealESRGAN_x2.pth", realesrgan_runner),
     "REAL-ESRGAN 4x": ("./assets/pretrained_models/RealESRGAN_x4.pth", realesrgan_runner),
     "REAL-ESRGAN 8x": ("./assets/pretrained_models/RealESRGAN_x8.pth", realesrgan_runner)
@@ -62,7 +62,7 @@ def load_face_enhancer_model(name='GFPGAN', device="cpu"):
         model = CodeFormerEnhancer(model_path=model_path, device=device)
     elif name == 'GFPGAN':
         model = gfpgan.GFPGANer(model_path=model_path, upscale=1, device=device)
-    elif name =='RestoreFormer':
+    elif name =='RESTOREFORMER PLUS PLUS':
         model = RestoreFormer(device, scale=1)
         model.load_weights(model_path, download=False)
     elif name == 'REAL-ESRGAN 4x':
@@ -71,9 +71,9 @@ def load_face_enhancer_model(name='GFPGAN', device="cpu"):
     elif name == 'REAL-ESRGAN 2x':
         model = RealESRGAN(device, scale=2)
         model.load_weights(model_path, download=False)
-    elif name == 'Real_Hatgan x4':
+    elif name == 'REAL_HATGAN x4':
         model = RealHatGAN(device, scale=4)
-    elif name == 'Ultra_Sharp x4':
+    elif name == 'ULTRA_SHARP x4':
         model = UltraShap(device, scale=4)
         model.load_weights(model_path, download=False)
     elif name == 'REAL-ESRGAN 4x':