add large file local

app.py

@@ -20,14 +20,14 @@ parser.add_argument('--contolnet_device', choices=['cuda', 'cpu'], default='cpu'
 
 args = parser.parse_args()
 
-# device = "cuda" if torch.cuda.is_available() else "cpu"
-device = "cpu"
+device = "cuda" if torch.cuda.is_available() else "cpu"
+# device = "cpu"
 
 if device == "cuda":
     args.image_caption_device = "cuda"
     args.dense_caption_device = "cuda"
     args.semantic_segment_device = "cuda"
-    args.contolnet_device = "cuda"
+    args.contolnet_device = "cpu"
 else:
     args.image_caption_device = "cpu"
     args.dense_caption_device = "cpu"

models/blip2_model.py

@@ -14,14 +14,14 @@ class ImageCaptioning:
             self.data_type = torch.float32
         else:
             self.data_type = torch.float16
-        # processor = Blip2Processor.from_pretrained("pretrained_models/blip2-opt-2.7b")
-        # model = Blip2ForConditionalGeneration.from_pretrained(
-        #     "pretrained_models/blip2-opt-2.7b", torch_dtype=self.data_type
-        # )
-        processor = Blip2Processor.from_pretrained("Salesforce/blip2-opt-2.7b")
+        processor = Blip2Processor.from_pretrained("pretrained_models/blip2-opt-2.7b")
         model = Blip2ForConditionalGeneration.from_pretrained(
-            "Salesforce/blip2-opt-2.7b", torch_dtype=self.data_type
+            "pretrained_models/blip2-opt-2.7b", torch_dtype=self.data_type
         )
+        # processor = Blip2Processor.from_pretrained("Salesforce/blip2-opt-2.7b")
+        # model = Blip2ForConditionalGeneration.from_pretrained(
+        #     "Salesforce/blip2-opt-2.7b", torch_dtype=self.data_type
+        # )
         model.to(self.device)
         return processor, model
 

models/controlnet_model.py

@@ -25,8 +25,8 @@ class TextToImage:
             map_location=self.device,  # Add this line
         ).to(self.device)
         pipeline = StableDiffusionControlNetPipeline.from_pretrained(
-            # "pretrained_models/stable-diffusion-v1-5",
-            "runwayml/stable-diffusion-v1-5",
+            "pretrained_models/stable-diffusion-v1-5",
+            # "runwayml/stable-diffusion-v1-5",
             controlnet=controlnet,
             safety_checker=None,
             torch_dtype=self.data_type,