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README.md

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----
-title: Test
-emoji: 🌖
-colorFrom: purple
-colorTo: blue
-sdk: gradio
-sdk_version: 5.43.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Test
+emoji: 🌖
+colorFrom: purple
+colorTo: blue
+sdk: gradio
+sdk_version: 5.43.1
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+from transformers import AutoModel
+import torch
+from PIL import Image
+import numpy as np
+import matplotlib.pyplot as plt
+
+# Carregar modelo Surya
+model_name = "nasa-ibm-ai4science/Surya-1.0"
+model = AutoModel.from_pretrained(model_name)
+model.eval()
+
+# Função para gerar heatmap
+def infer_solar_image_heatmap(img):
+    # Pré-processamento: grayscale, resize 224x224
+    img = img.convert("L").resize((224, 224))
+    img_tensor = torch.tensor(np.array(img), dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.0
+
+    with torch.no_grad():
+        outputs = model(img_tensor)
+    
+    # Pegar os primeiros canais e reshapar para visualização
+    emb = outputs[0].squeeze().numpy()
+    heatmap = emb - emb.min()
+    heatmap /= heatmap.max() + 1e-8  # normalização 0-1
+
+    # Criar figura
+    plt.imshow(heatmap, cmap='hot')
+    plt.axis('off')
+    plt.tight_layout()
+    
+    # Salvar figura em buffer
+    fig = plt.gcf()
+    return fig
+
+# Interface Gradio
+interface = gr.Interface(
+    fn=infer_solar_image_heatmap,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Plot(label="Heatmap do embedding Surya"),
+    title="Playground Surya-1.0 com Heatmap",
+    description="Upload de imagem solar → visualize heatmap gerado pelo Surya-1.0"
+)
+
+interface.launch()

requirements.txt

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+torch
+transformers
+pillow
+numpy
+matplotlib
+gradio