def lambda_handler(event, context):
try:
body = json.loads(event['body'])
url = body['url']
except Exception as e:
return {
'statusCode': 400,
'body': 'Cannot get url from request: %s' % e,
}
img_data = urllib.request.urlopen(url)
img, bitmap = image.read_image(img_data)
cells = grid.detect_filled_cells(bitmap)
sudoku = [[0 for _ in range(9)] for _ in range(9)]
for cell in cells:
value = digit.predict(cell[0])
pos = cell[2]
sudoku[pos[0]][pos[1]] = int(value)
result = copy.deepcopy(sudoku)
if not solver.solve(result):
result = None
return {
'statusCode': 200,
'headers': {
'Access-Control-Allow-Headers': 'Content-Type',
'Access-Control-Allow-Origin': '*',
'Access-Control-Allow-Methods': 'OPTIONS,POST',
},
'body': json.dumps({
'input': sudoku,
'solved': result,
}),
}
def test_detection(example, ext):
im, a = image.read_image(f'data/sudoku{example}.{ext}')
expected_cells = eval(open(f'data/sudoku{example}.gold').read())
cells = grid.detect_filled_cells(a)
# Cell coordinates and positions should be as expected
coords = [c[1] for c in cells]
pos = [c[2] for c in cells]
assert coords == expected_cells['coords']
assert pos == expected_cells['pos']
def upload():
if request.files['image']:
# 画像として読み込み
img = read_image(request.files['image'])
# 変換
img, kanna_value, original_image = pred_kanna(img)
# オリジナル画像を保存
save_filename, save_path = save_image(kanna_value, original_image)
return render_template('result.html', filename=save_filename, kanna_value=kanna_value)
def load_images():
images = []
print('Loading Images')
for breed in os.listdir('data/Annotation/'):
for dog in os.listdir('data/Annotation/' + breed):
tree = et.parse('data/Annotation/' + breed + '/' + dog)
root = tree.getroot()
objects = root.findall('object')
for o in objects:
box = o.find('bndbox')
xmin = int(box.find('xmin').text)
ymin = int(box.find('ymin').text)
xmax = int(box.find('xmax').text)
ymax = int(box.find('ymax').text)
bounds = (xmin, ymin, xmax, ymax)
try:
image = read_image('data/all-dogs/' + dog + '.jpg', bounds)
images.append(image)
except:
print('No image', dog)
return np.array(images)
@simple_time_tracker()
def count_image_pixels_over_threshold(im, threshold=250):
"""计算大于某个色差值的所有像素比
"""
pixels = im.width * im.height
hit = 0
ml = im.height
part_list = [[0, ml // 4], [ml // 4, ml // 2], [ml // 2, ml - ml // 4],
[ml - ml // 4, ml]]
with concurrent.futures.ProcessPoolExecutor() as executor:
results = [
executor.submit(count_hit_fast, im, (im.width, part[1]), threshold)
for part in part_list
]
for rc in concurrent.futures.as_completed(results):
part_hits = rc.result()
hit += part_hits
ratio = hit / pixels
return [hit, pixels, ratio]
if __name__ == '__main__':
im = read_image("WechatIMG7.jpeg")
hit, pixels, ratio = count_image_pixels_over_threshold(im)
print(f"White pixels: hit = {hit}, pixels = {pixels}, ratio = {ratio}")
return image
def profile_measurement(self, frame):
points3d, profile = self.points_profile(frame)
frame = self.draw_points(frame, profile,
color=(0, 0, 255), thickness=2)
if len(points3d) > 0:
print points3d
point3d = points3d[len(points3d)/5]
cv2.putText(frame, '%s' % point3d, (11, 22),
cv2.FONT_HERSHEY_PLAIN, 1.0, (0, 255, 255),
thickness=1, lineType=cv2.CV_AA)
return frame
if __name__ == '__main__':
import image
img = image.read_image('../data/utest9.png')
profile0 = Profile(axis=1, thr=180, method='pcog')
image.show_image(profile0.profile_measurement(img))
#cv2.imwrite('peak.png', profile0.profile_measurement(img))
#profile0.load_configuration('triangulation0.yml')
# Camera test
#from webcam import Webcam
#camera = Webcam(device=1)
#camera.set_size((800, 600))
#camera.set_parameters(0.30, 0.20, 0.10)
#camera.run(callback=lambda img: profile0.profile_measurement(img))
def test_read_image():
im, a = image.read_image('data/sudoku1.jpg')
assert (im.width, im.height) == (298, 298)
assert a.shape == (298, 298)
from image import read_image, show_image, show_images
def transform(np_array, shape):
return np_array.reshape(shape).astype('uint8')
if __name__ == '__main__':
if len(sys.argv) > 1:
image_file_name = sys.argv[1]
else:
raise Exception('Missing image file name')
img, original_shape = read_image(image_file_name)
hill = Hill(data=img, file_name=image_file_name)
### Testing zone
print(img.shape)
# -----------------------------------------------------------------
# -------------------- Parte de codificación-----------------------
# -----------------------------------------------------------------
# Obtener la imagen vectorial codificada
encoded_image_vector = hill.encode(img[0])
# Cambiar la forma original de la imagen
encoded_image = encoded_image_vector.reshape(original_shape)
return image
def profile_measurement(self, frame):
points3d, profile = self.points_profile(frame)
frame = self.draw_points(frame, profile,
color=(0, 0, 255), thickness=2)
if len(points3d) > 0:
print points3d
point3d = points3d[len(points3d)/5]
cv2.putText(frame, '%s' % point3d, (11, 22),
cv2.FONT_HERSHEY_PLAIN, 1.0, (0, 255, 255),
thickness=1, lineType=cv2.CV_AA)
return frame
if __name__ == '__main__':
import image
img = image.read_image('../data/utest9.png')
profile0 = Profile(axis=1, thr=180, method='pcog')
image.show_image(profile0.profile_measurement(img))
#cv2.imwrite('peak.png', profile0.profile_measurement(img))
#profile0.load_configuration('triangulation0.yml')
# Camera test
#from webcam import Webcam
#camera = Webcam(device=1)
#camera.set_size((800, 600))
#camera.set_parameters(0.30, 0.20, 0.10)
#camera.run(callback=lambda img: profile0.profile_measurement(img))