Update model.py

model.py

@@ -0,0 +1,35 @@
+import requests
+from PIL import Image
+from transformers import BlipProcessor, BlipForConditionalGeneration
+
+# Initialize processor and model
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large").to("cuda")
+
+# Function to process and caption an image from a URL
+def caption_image(image_url):
+    try:
+        # Load image from the provided URL
+        raw_image = Image.open(requests.get(image_url, stream=True).raw).convert('RGB')
+        
+        # Conditional image captioning
+        text = "a photography of"
+        inputs = processor(raw_image, text, return_tensors="pt").to("cuda")
+        out = model.generate(**inputs)
+        conditional_caption = processor.decode(out[0], skip_special_tokens=True)
+
+        # Unconditional image captioning
+        inputs = processor(raw_image, return_tensors="pt").to("cuda")
+        out = model.generate(**inputs)
+        unconditional_caption = processor.decode(out[0], skip_special_tokens=True)
+
+        # Print the results
+        print("Conditional Caption:", conditional_caption)
+        print("Unconditional Caption:", unconditional_caption)
+    
+    except Exception as e:
+        print(f"Error occurred: {e}")
+
+# Get image URL from user input
+image_url = input("Enter the image URL: ")
+caption_image(image_url)