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from flask import Flask, request |
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import numpy as np |
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import tensorflow as tf |
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import cv2 |
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app = Flask(__name__) |
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loaded_CNN = tf.keras.models.load_model('CNN_extended_dataset.h5') |
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@app.route('/get-prediction', methods = ['POST']) |
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def get_prediction(): |
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img_array = request.json.get('data') |
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img_array = np.array(img_array, dtype=np.uint8).reshape(400, 400) |
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img_array = cv2.resize(img_array, (28, 28)) |
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img_array = img_array.reshape(1, 28, 28) |
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pred = loaded_CNN.predict([img_array]) |
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final_pred = np.argmax(pred) |
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return str(final_pred) |
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if __name__ == '__main__': |
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app.run() |
