Create app.py

app.py

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+import gradio as gr
+import matplotlib.pyplot as plt
+import numpy as np
+from datasets import load_dataset
+
+# Load the chest X-ray classification dataset
+dataset = load_dataset("keremberke/chest-xray-classification")
+
+def show_samples(label):
+    # Get samples from the dataset
+    images = []
+    for i in range(5):  # Show 5 images
+        images.append(dataset['train'][i]['image'])  # Adjust as needed
+
+    # Create a grid of images
+    fig, axes = plt.subplots(1, 5, figsize=(15, 5))
+    for ax, img in zip(axes, images):
+        ax.imshow(np.asarray(img))  # Convert to a format suitable for matplotlib
+        ax.axis('off')
+    plt.title(f"Label: {label}")
+    plt.tight_layout()
+    plt.show()
+
+# Create Gradio interface
+iface = gr.Interface(fn=show_samples, inputs="text", outputs="plot")
+iface.launch()