Create app.py

app.py

@@ -0,0 +1,27 @@
+import gradio as gr
+from transformers import BlipProcessor, BlipForConditionalGeneration
+from PIL import Image
+import torch
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+# Load fine-tuned model from HF Hub
+model = BlipForConditionalGeneration.from_pretrained("omarkashif/blip-finetuned-flickr30k").to(device)
+processor = BlipProcessor.from_pretrained("omarkashif/blip-finetuned-flickr30k")
+
+def generate_caption(image):
+    image = image.convert("RGB")
+    inputs = processor(images=image, return_tensors="pt").to(device)
+    with torch.no_grad():
+        output = model.generate(**inputs, max_length=40, num_beams=5)
+    caption = processor.decode(output[0], skip_special_tokens=True)
+    return caption
+
+# Gradio UI
+gr.Interface(
+    fn=generate_caption,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="BLIP Fine-Tuned Caption Generator",
+    description="Upload an image to generate a caption using a BLIP model fine-tuned on Flickr30k."
+).launch()