Added image captioning

app.py

@@ -1,7 +1,37 @@
+from PIL import Image
+from transformers import BlipProcessor, BlipForConditionalGeneration
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Initialization of the BLIP processor and model
+processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large")
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+def generate_captions(image, text=""):
+    # Convert the uploaded image to PIL Image
+    raw_image = Image.fromarray(image).convert('RGB')
+    
+    if text:  # Conditional image captioning
+        inputs = processor(raw_image, text, return_tensors="pt")
+    else:  # Unconditional image captioning
+        inputs = processor(raw_image, return_tensors="pt")
+    
+    # Generate captions for the image
+    out = model.generate(**inputs)
+    caption = processor.decode(out[0], skip_special_tokens=True)
+    
+    return caption
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=generate_captions,
+    inputs=[
+        gr.Image(label="Upload/Drag Image"),  # Removed the 'tool' argument
+        gr.Textbox(label="Conditional Text (optional)", placeholder="Enter conditional text (optional)...")
+    ],
+    outputs=gr.Textbox(label="Generated Caption"),
+    title="BLIP Image Caption Generator",
+    description="This app generates captions for uploaded images. You can also provide conditional text to guide the caption generation."
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

@@ -1,5 +1,5 @@
-# diffusers
-# gradio
-# torch
-# transformers
-# Pillow
+diffusers
+gradio
+torch
+transformers
+Pillow