hw6

infer.py

@@ -38,7 +38,7 @@ LoRA_path = 'new_model'
 CONTROLNET_MODE = {
     "Canny Edge Detection" : "lllyasviel/control_v11p_sd15_canny",
     "Pixel to Pixel": "lllyasviel/control_v11e_sd15_ip2p",
-    "HED edge detection (soft edge)" : "lllyasviel/control_sd15_hed",
+    "HED edge detection (soft edge)" : "lllyasviel/control_v11p_sd15_softedge",
     "Midas depth estimation" : "lllyasviel/control_v11f1p_sd15_depth",
     "Surface Normal Estimation" : "lllyasviel/control_v11p_sd15_normalbae",
     "Scribble-Based Generation" : "lllyasviel/control_v11p_sd15_scribble",
@@ -138,7 +138,7 @@ def prepare_controlnet_image(controlnet_image, mode):
         image = Image.fromarray(image)
 
     elif mode == "Pixel to Pixel":
-        image = controlnet_image.convert('RGB')
+        image = Image.fromarray(controlnet_image).convert('RGB')
 
     elif mode == "HED edge detection (soft edge)":
         processor = HEDdetector.from_pretrained('lllyasviel/Annotators')
@@ -146,7 +146,7 @@ def prepare_controlnet_image(controlnet_image, mode):
 
     elif mode == "Midas depth estimation":
         depth_estimator = pipeline('depth-estimation')
-        image = depth_estimator(controlnet_image)['depth']
+        image = depth_estimator(Image.fromarray(controlnet_image))['depth']
         image = np.array(image)
         image = image[:, :, None]
         image = np.concatenate([image, image, image], axis=2)