Create app.py

app.py

@@ -0,0 +1,64 @@
+import transformers
+import torch
+import gradio as gr
+import requests
+
+from transformers import BlipForImageTextRetrieval
+from transformers import AutoProcessor
+from transformers.utils import logging
+from PIL import Image
+
+model = BlipForConditionalGeneration.from_pretrained(
+    "Salesforce/blip-image-captioning-base")
+processor = AutoProcessor.from_pretrained(
+    "Salesforce/blip-image-captioning-base")
+
+def process_image(input_type, image_url, image_upload):
+    if input_type == "URL":
+        raw_image =  Image.open(requests.get(image_url, stream=True).raw).convert('RGB')
+    else:
+        raw_image = image_upload
+
+    inputs = processor(raw_image,return_tensors="pt")
+    out = model.generate(**inputs)[0]
+    description = processor.decode(out, skip_special_tokens=True).capitalize()
+
+    formatted_description = (
+        f"""<div><h1 style='text-align: center; font-size: 40px; color: orange;'>
+        {description}
+        </h1></div>"""
+    )
+    return formatted_description
+
+def display_image_from_url(image_url):
+    if image_url:
+        image = Image.open(requests.get(image_url, stream=True).raw).convert('RGB')
+        return image
+    return None
+
+def toggle_inputs(input_type):
+    if input_type == "URL":
+        return gr.update(visible=True), gr.update(visible=True), gr.update(visible=False)
+    else:
+        return gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+    """
+    # Image Captioning - test & demo app by Srinivas.V..
+    Paste either URL of an image or upload the image and submit.
+    """)
+
+    input_type = gr.Radio(choices=["URL", "Upload"], label="Input Type")
+    image_url = gr.Textbox(label="Image URL", visible=False)
+    url_image = gr.Image(type="pil", label="URL Image", visible=False)
+    image_upload = gr.Image(type="pil", label="Upload Image", visible=False)
+
+    input_type.change(fn=toggle_inputs, inputs=input_type, outputs=[image_url, url_image, image_upload])
+    image_url.change(fn=display_image_from_url, inputs=image_url, outputs=url_image)
+
+    submit_btn = gr.Button("Submit")
+    processed_image = gr.HTML(label="Caption for the Image")
+    submit_btn.click(fn=process_image, inputs=[input_type, image_url, image_upload], outputs=processed_image)
+
+demo.launch(debug=True, share=True)