diff --git a/adapter.py b/adapter.py
new file mode 100644
index 00000000..e173f723
--- /dev/null
+++ b/adapter.py
@@ -0,0 +1,28 @@
+import base64
+import json
+
+import cv2
+import sys
+import numpy as np
+
+from runner import warp_board
+
+
+# Load base64 encoded image from stdin
+stdin = sys.stdin.readline()
+stdin_decoded = base64.b64decode(stdin)
+img_array = np.frombuffer(stdin_decoded, dtype=np.uint8)
+camera_img = cv2.imdecode(img_array, flags=cv2.IMREAD_COLOR)
+
+# Warp board, saving the homography points as well
+src_points = dst_points = []
+warped = warp_board(camera_img, src_points=src_points, dst_points=dst_points)
+
+
+# Finally, output to stdout for unity to read
+result = {
+    "src_points": [p.tolist() for p in src_points],
+    "dst_points": [p.tolist() for p in dst_points],
+}
+
+print(json.dumps(result))
diff --git a/runner.py b/runner.py
index a69ee945..9c3d7fa8 100644
--- a/runner.py
+++ b/runner.py
@@ -131,7 +131,7 @@ def train_pieces_svm_canny() -> None:
         joblib.dump(classifier, f"classifiers/classifier_empty/white_piece_on_{square_color}_square.pkl")
 
 
-def warp_board(camera_image, debug_image=None) -> np.ndarray:
+def warp_board(camera_image, debug_image=None, src_points: list = None, dst_points: list = None) -> np.ndarray:
     baseline = cv2.imread("new_baseline_board.png")
 
     camera_image_gray = cv2.cvtColor(camera_image, cv2.COLOR_BGR2GRAY)
@@ -188,6 +188,11 @@ def warp_board(camera_image, debug_image=None) -> np.ndarray:
         points1[i, :] = camera_image_keypoints[m.queryIdx].pt
         points2[i, :] = baseline_keypoints[m.trainIdx].pt
 
+    if src_points is not None:
+        src_points.extend(points1)
+    if dst_points is not None:
+        dst_points.extend(points2)
+
     h, mask = cv2.findHomography(points1, points2, cv2.RANSAC)
 
     height, width, channels = baseline.shape