Web.

adapter.py

@@ -10,8 +10,6 @@ from runner import find_homography, warp_board
 from tensor_classifier import predict_board
 
 
-while True:
-    try:
 stdin = sys.stdin.readline()
 stdin_decoded = base64.b64decode(stdin)
 img_array = np.frombuffer(stdin_decoded, dtype=np.uint8)
@@ -31,6 +29,3 @@ while True:
 }
 
 print(json.dumps(result))
-        exit()  # TODO
-    except Exception as e:
-        print(e)

web.py

@@ -0,0 +1,41 @@
+import base64
+
+import cv2
+import numpy as np
+from flask import Flask, jsonify, request
+
+from main import find_occupied_squares
+from runner import find_homography, warp_board
+from tensor_classifier import predict_board
+
+app = Flask(__name__)
+
+
+@app.route("/", methods=["POST"])
+def process():
+    data = request.get_json(force=True)
+
+    decoded = base64.b64decode(data["img"])
+    img_array = np.frombuffer(decoded, dtype=np.uint8)
+    camera_img = cv2.imdecode(img_array, flags=cv2.COLOR_BGR2RGB)
+    camera_img = cv2.cvtColor(camera_img, cv2.COLOR_BGR2RGB)
+
+    # def do_everything:
+    homography = find_homography(camera_img)
+    warped_board = warp_board(camera_img, homography)
+    occupied_squares = find_occupied_squares(warped_board)
+    board = predict_board(occupied_squares)
+
+    # Finally, output for unity to read
+    return jsonify({
+        "homography": homography.tolist(),
+        "board": board.to_array,
+    })
+
+
+def main():
+    app.run(host='0.0.0.0', debug=True)
+
+
+if __name__ == '__main__':
+    main()