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Adapter works. Btw when you look in the commit graph to see how much Alexander did, remember that this was Casper's commit.

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Alexander Munch-Hansen 2019-04-11 14:25:48 +02:00
parent d3d2d362a6
commit 7d03937526
2 changed files with 15 additions and 10 deletions
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19
adapter.py
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@ -1,25 +1,28 @@
import base64
import json import json
import cv2 import cv2
import sys
import numpy as np import numpy as np
from runner import warp_board from runner import warp_board
# Run this script as: 'python3 adapter.py < ~/Pictures/board.png' or pipe a binary image to stdin
# Load binary image from stdin # Load base64 encoded image from stdin
with open(0, "rb") as stdin: stdin = sys.stdin.readline()
array = np.frombuffer(stdin.read(), dtype='uint8') stdin_decoded = base64.b64decode(stdin)
camera_img = cv2.imdecode(array, flags=cv2.IMREAD_COLOR) 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 # Warp board, saving the homography points as well
points = [] src_points = dst_points = []
warped = warp_board(camera_img, dst_points=points) warped = warp_board(camera_img, src_points=src_points, dst_points=dst_points)
# Finally, output to stdout for unity to read # Finally, output to stdout for unity to read
result = { result = {
"points": points "src_points": [p.tolist() for p in src_points],
"dst_points": [p.tolist() for p in dst_points],
} }
print(json.dumps(result)) print(json.dumps(result))

6
runner.py
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@ -131,7 +131,7 @@ def train_pieces_svm_canny() -> None:
joblib.dump(classifier, f"classifiers/classifier_empty/white_piece_on_{square_color}_square.pkl") joblib.dump(classifier, f"classifiers/classifier_empty/white_piece_on_{square_color}_square.pkl")
def warp_board(camera_image, debug_image=None, dst_points: list = 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") baseline = cv2.imread("new_baseline_board.png")
camera_image_gray = cv2.cvtColor(camera_image, cv2.COLOR_BGR2GRAY) camera_image_gray = cv2.cvtColor(camera_image, cv2.COLOR_BGR2GRAY)
@ -188,8 +188,10 @@ def warp_board(camera_image, debug_image=None, dst_points: list = None) -> np.nd
points1[i, :] = camera_image_keypoints[m.queryIdx].pt points1[i, :] = camera_image_keypoints[m.queryIdx].pt
points2[i, :] = baseline_keypoints[m.trainIdx].pt points2[i, :] = baseline_keypoints[m.trainIdx].pt
if src_points is not None:
src_points.extend(points1)
if dst_points is not None: if dst_points is not None:
dst_points.extend(zip(points1, points2)) dst_points.extend(points2)
h, mask = cv2.findHomography(points1, points2, cv2.RANSAC) h, mask = cv2.findHomography(points1, points2, cv2.RANSAC)