Update app.py

app.py

@@ -1,14 +1,17 @@
-from diffusers import DiffusionPipeline
+from transformers import pipeline
 import gradio as gr
-model_id = "CompVis/ldm-text2im-large-256"
-ldm = DiffusionPipeline.from_pretrained(model_id)
-
-
-def generate_image(Prompt):
- images = ldm([Prompt], num_inference_steps=50, eta=.3, guidance_scale=6)
- return images.images[0]
-
-    
-interface = gr.Interface(fn = generate_image,inputs = "text",outputs = "image",title = "Mashdemy Demo Image Generator App", description = "Type in a text and click submit to generate an image:", examples = ["a clown reading a book", "a cat using a laptop", "An elephant on grass"])
-
-interface.launch(share = True)
+from PIL import Image
+pipe = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large")
+def generate_caption(image):
+    # Generate a caption for the image
+    captions = pipe(image)
+    return captions[0]['generated_text']
+demo = gr.Interface(
+    fn=generate_caption,
+    inputs=gr.Image(type="pil", label="Upload an Image"),
+    outputs=gr.Textbox(label="Generated Caption"),
+title="Image Caption Generator",
+    description="Upload an image to generate a caption using the BLIP model."
+)
+if __name__ == "__main__":
+    demo.launch(share=True)