Create app.py

app.py

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+import gradio as gr
+import requests
+from PIL import Image
+from io import BytesIO
+import numpy as np
+import torch
+from skillful_nowcasting.dgmr import DGMR
+from datetime import datetime, timezone
+
+# Load the pretrained model
+model = DGMR.from_pretrained("openclimatefix/dgmr")
+
+def get_latest_radar_image():
+    """Fetches the latest radar image from the Iowa State University archive."""
+    now = datetime.now(timezone.utc)
+    url = f"https://mesonet.agron.iastate.edu/archive/data/{now.year}/{now.month:02d}/{now.day:02d}/GIS/uscomp/n0r_0.png"
+    response = requests.get(url)
+    img = Image.open(BytesIO(response.content)).convert("RGB")
+    return img
+
+def preprocess_image(img):
+    """Preprocesses the image for the model."""
+    img = img.resize((128, 128))
+    img_array = np.array(img) / 255.0
+    img_tensor = torch.from_numpy(img_array).permute(2, 0, 1).float()
+    # Add batch and sequence dimensions
+    return img_tensor.unsqueeze(0).unsqueeze(0)
+
+def postprocess_output(output_tensor):
+    """Postprocesses the model output back to an image."""
+    # Take the first prediction in the sequence
+    output_tensor = output_tensor[0, 0, :, :, :]
+    output_array = output_tensor.permute(1, 2, 0).detach().numpy()
+    output_array = (output_array * 255).astype(np.uint8)
+    return Image.fromarray(output_array)
+
+def predict_nowcast():
+    """Fetches the latest radar, runs the nowcasting model, and returns the images."""
+    input_image = get_latest_radar_image()
+    preprocessed_input = preprocess_image(input_image)
+    
+    # The DGMR model expects a sequence of 4 input images.
+    # For this example, we will feed the same image 4 times.
+    model_input = torch.cat([preprocessed_input] * 4, dim=1)
+    
+    with torch.no_grad():
+        output = model(model_input)
+    
+    predicted_image = postprocess_output(output)
+    
+    return input_image, predicted_image
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("## American Radar Nowcasting with AI")
+    gr.Markdown(
+        "Click the button to fetch the latest American radar image and generate a nowcast prediction using the `skillful_nowcasting` model."
+    )
+    
+    with gr.Row():
+        input_image_display = gr.Image(label="Current Radar Image")
+        output_image_display = gr.Image(label="Predicted Nowcast")
+
+    predict_button = gr.Button("Generate Nowcast")
+    predict_button.click(
+        fn=predict_nowcast,
+        inputs=[],
+        outputs=[input_image_display, output_image_display]
+    )
+
+demo.launch()