Create app.py

app.py

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+import torch
+from transformers import Blip2Processor, Blip2ForConditionalGeneration
+from PIL import Image
+import gradio as gr
+from io import BytesIO
+import requests
+
+# -----------------------------
+# Device and Model Setup
+# -----------------------------
+device = "cuda" if torch.cuda.is_available() else "cpu"
+print(f"Using device: {device}")
+
+model_name = "Salesforce/blip2-flan-t5-xl-coco"  # public model
+processor = Blip2Processor.from_pretrained(model_name)
+model = Blip2ForConditionalGeneration.from_pretrained(model_name)
+model.to(device)
+
+# -----------------------------
+# Inference Function
+# -----------------------------
+def analyze_eo_image(image, question):
+    if image is None or question.strip() == "":
+        return "Please upload an EO image and ask a question."
+
+    if image.mode != "RGB":
+        image = image.convert("RGB")
+
+    inputs = processor(image, question, return_tensors="pt").to(
+        device, torch.float16 if device=="cuda" else torch.float32
+    )
+
+    out = model.generate(
+        **inputs,
+        max_new_tokens=80,
+        do_sample=True,
+        temperature=0.7
+    )
+
+    return processor.decode(out[0], skip_special_tokens=True)
+
+# -----------------------------
+# Optional: URL input
+# -----------------------------
+def analyze_eo_url(url, question):
+    try:
+        response = requests.get(url)
+        image = Image.open(BytesIO(response.content)).convert("RGB")
+        return analyze_eo_image(image, question)
+    except Exception as e:
+        return f"Error loading image: {e}"
+
+# -----------------------------
+# Beautiful Gradio Layout
+# -----------------------------
+with gr.Blocks(title="🌍 EO Image Analysis") as demo:
+
+    gr.Markdown(
+        """
+        # 🌍 Earth Observation Image Analysis
+        Ask questions about EO images using a multimodal AI model.
+        Powered by BLIP-2 + FLAN-T5.
+        **Examples:** "Identify land cover types", "Where is the river?", "Has urban area expanded?"
+        """
+    )
+
+    with gr.Tabs():
+        with gr.Tab("Upload Image"):
+            with gr.Row():
+                with gr.Column(scale=1):
+                    img_input = gr.Image(type="pil", label="Upload EO Image")
+                    question_input = gr.Textbox(label="Ask a question about the image", placeholder="E.g. Where is the river?")
+                    submit_btn = gr.Button("Analyze 🌟")
+                with gr.Column(scale=1):
+                    output_text = gr.Textbox(label="AI Answer", interactive=False)
+
+            submit_btn.click(analyze_eo_image, inputs=[img_input, question_input], outputs=output_text)
+
+        with gr.Tab("Use Image URL"):
+            with gr.Row():
+                with gr.Column(scale=1):
+                    url_input = gr.Textbox(label="Enter Image URL")
+                    url_question = gr.Textbox(label="Ask a question about the image")
+                    url_btn = gr.Button("Analyze 🌟")
+                with gr.Column(scale=1):
+                    url_output = gr.Textbox(label="AI Answer", interactive=False)
+
+            url_btn.click(analyze_eo_url, inputs=[url_input, url_question], outputs=url_output)
+
+    gr.Markdown(
+        "💡 Tip: Use clear, simple questions for best results. Supports natural language queries about EO images."
+    )
+
+demo.launch(share=True)