Initial commit

.gitignore

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+venv

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Initialize the image classification pipeline
+classifier = pipeline("image-classification")
+# Alternatively you can define what model should the pipeline use, sometimes it requires that you login with your token
+#classifier = pipeline("image-classification", model="microsoft/resnet-50")
+
+#print(classifier.model)
+
+def classify_image(image):
+    results = classifier(image)
+    # Get the top prediction
+    top_result = results[0]
+    label = top_result['label']
+    score = top_result['score']
+    return f"Label: {label}, Confidence: {score:.2f}"
+
+iface = gr.Interface(
+    fn=classify_image,
+    inputs=gr.Image(type="pil", label="Upload an Image"),
+    outputs=gr.Textbox(label="Prediction"),
+    title="Image Classifier"
+)
+
+iface.launch()

requirements.txt

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+transformers
+torch
+torchvision