upload flask api

Dockerfile

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+# read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+EXPOSE 5000
+CMD ["python", "api.py"]

api.py

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+from flask import Flask, request, jsonify
+from huggingface_hub import from_pretrained_keras
+import numpy as np
+from PIL import Image
+import io
+
+app = Flask(__name__)
+
+# Load the model
+model = from_pretrained_keras("MissingBreath/recycle-garbage-model")
+
+# Class labels
+# class_labels = ['cardboard', 'glass', 'metal', 'paper', 'plastic', 'trash']
+
+@app.route('/classify', methods=['POST'])
+def classify():
+    file = request.files['image']
+    if file:
+        img = Image.open(io.BytesIO(file.read()))
+        img = img.resize((128, 128))
+        img_array = np.array(img) / 255.0
+        img_array = np.expand_dims(img_array, axis=0)
+        predictions = model.predict(img_array)
+        predicted_class_idx = np.argmax(predictions)
+        # predicted_class = class_labels[predicted_class_idx]
+        # return jsonify({'prediction': predicted_class})
+        return jsonify({'prediction': predicted_class_idx})
+    else:
+        return jsonify({'error': 'No image provided'}), 400
+
+if __name__ == '__main__':
+    app.run(debug=True)

requirements.txt

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+flask
+numpy
+pillow
+huggingface_hub