MVP

nft_svc/app.py

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+import base64
+import io
+
+from PIL import Image
+from flask import Flask, request, jsonify
+import matplotlib.image as mpimg
+import numpy as np
+import numba
+
+app = Flask(__name__)
+
+
+@numba.njit
+def optimized_mandelbrot(n_rows, n_columns, iterations, cx, cy):
+    x_cor = np.linspace(-2, 2, n_rows)
+    y_cor = np.linspace(-2, 2, n_columns)
+    output = np.zeros((n_rows,n_columns))
+    c = cx + 1j * cy
+    for i in range(n_rows):
+        for j in range(n_columns):
+            z = x_cor[i] + y_cor[j] * 1j
+            count = 0
+            for k in range(iterations):
+                z = (z*z) + c
+                count += 1
+                if np.abs(z) > 4:
+                    break
+            output[i, j] = count
+    return output.T
+
+
+def open_image_as_array(path):
+    return mpimg.imread(path)
+
+
+def get_encoded_img(arr):
+    img = Image.fromarray(arr).convert("L")
+    img_byte_arr = io.BytesIO()
+    img.save(img_byte_arr, format='PNG')
+    encoded_img = base64.encodebytes(img_byte_arr.getvalue()).decode('ascii')
+    return encoded_img
+
+
+@app.route('/getImage', methods=['GET'])
+def get_image():
+    name = request.args.get('name')
+    fractal = optimized_mandelbrot(1000, 1000, np.random.randint(2, 251), np.random.uniform(-1, 1), np.random.uniform(-1, 1))
+    img = get_encoded_img(fractal)
+    return jsonify({
+        "code": 0,
+        "image": img,
+        "first_time": 1
+    })
+
+
+def start_app():
+    app.run()
+
+
+if __name__ == '__main__':
+    start_app()