66 lines
1.5 KiB
Python
66 lines
1.5 KiB
Python
import io
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import random
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from PIL import Image
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from flask import Flask, request, jsonify
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import matplotlib.image as mpimg
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import numpy as np
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import numba
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import pickle
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import base64
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app = Flask(__name__)
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@numba.njit
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def optimized_mandelbrot(n_rows, n_columns, iterations, cx, cy):
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x_cor = np.linspace(-2, 2, n_rows)
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y_cor = np.linspace(-2, 2, n_columns)
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output = np.zeros((n_rows,n_columns))
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c = cx + 1j * cy
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for i in range(n_rows):
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for j in range(n_columns):
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z = x_cor[i] + y_cor[j] * 1j
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count = 0
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for k in range(iterations):
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z = (z*z) + c
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count += 1
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if np.abs(z) > 4:
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break
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output[i, j] = count
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return output.T
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def open_image_as_array(path):
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return mpimg.imread(path)
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def get_encoded_img(arr):
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img = Image.fromarray(arr).convert("L")
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img_byte_arr = io.BytesIO()
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img.save(img_byte_arr, format='PNG')
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encoded_img = base64.encodebytes(img_byte_arr.getvalue()).decode('ascii')
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return encoded_img
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@app.route('/getImage', methods=['GET'])
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def get_image():
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with open('data_100.pickle', 'rb') as f:
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images = pickle.load(f)
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buffered = io.BytesIO()
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random.choice(images).save(buffered, format="JPEG")
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img_str = base64.b64encode(buffered.getvalue())
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return jsonify({
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"code": 0,
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"image": str(img_str.decode('ascii')),
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"first_time": 1
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})
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def start_app():
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app.run()
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if __name__ == '__main__':
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start_app()
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