Create app.py

app.py

@@ -0,0 +1,34 @@
+import gradio as gr
+from transformers import pipeline
+import requests
+from io import BytesIO
+from PIL import Image
+import pyttsx3  # Text-to-speech (optional)
+
+# --- Load hosted model ---
+captioner = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
+
+# --- Caption & TTS function ---
+def generate_caption_tts(image):
+    # If user uploads a URL
+    if isinstance(image, str):
+        image = Image.open(BytesIO(requests.get(image).content))
+    caption = captioner(image)[0]['generated_text']
+    
+    # TTS (optional)
+    tts = pyttsx3.init()
+    tts.say(caption)
+    tts.runAndWait()
+    
+    return caption
+
+# --- Gradio interface ---
+iface = gr.Interface(
+    fn=generate_caption_tts,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Image Captioning for Visually Impaired",
+    description="Upload any image and get a descriptive caption."
+)
+
+iface.launch()