def detect_image_in_container(blob_name, should_upload, container_service):
bytes = container_service.download_blob(blob_name)
image = get_image_from_bytes_string(bytes)
for color in COLORS:
image_binary_where_color = np.zeros(image.shape[0:2], dtype=np.uint8)
for bound in color.bounds:
image_binary_where_color_bound = find_color_in_image(
image, np.array(bound.lower), np.array(bound.upper))
image_binary_where_color = np.bitwise_or(
image_binary_where_color, image_binary_where_color_bound)
biggest_contour = get_biggest_contour_in_range(
image_binary_where_color)
if len(biggest_contour) > 0:
bounding_box_xywh = cv2.boundingRect(biggest_contour)
draw_bounding_box(
image,
bounding_box_xywh,
f"{color.name} ziptie",
color.default_color,
)
if should_upload:
image_file_extension = f".{blob_name.split('.')[-1]}"
image_file_name = blob_name.split("/")[-1]
bytes_string = get_bytes_string_from_image(image, image_file_extension)
blob_client = container_service.get_blob_client(
f"processed_images/{image_file_name}")
blob_client.upload_blob(bytes_string, overwrite=True)
else:
show_image(image)
def draw_all(image, boxes, score=None, class_num=None):
show_image(
draw_boxes((image - 127.5) / 127.5,
boxes[:, 0:4],
class_num=class_num,
score=score,
blue=255,
green=0,
red=0))
def main():
images_dir = input("Please enter the directory containing the shredded images to be reassembled: ")
filenames = files_in_directory(images_dir)
print("files to be reassembled: {0}".format(filenames))
slices = []
for filename in filenames:
slices.append(load_image(filename))
#show_all_images(slices[0], tuple(slices[1:]))
while len(slices) > 1:
left_index, right_index = findBestMatch(slices)
print((left_index, right_index))
merge(slices, left_index, right_index)
show_image(slices[0])
def main():
images_dir = input(
"Please enter the directory containing the shredded images to be reassembled: "
)
filenames = files_in_directory(images_dir)
print("files to be reassembled: {0}".format(filenames))
slices = []
for filename in filenames:
slices.append(load_image(filename))
#show_all_images(slices[0], tuple(slices[1:]))
while len(slices) > 1:
left_index, right_index = findBestMatch(slices)
print((left_index, right_index))
merge(slices, left_index, right_index)
show_image(slices[0])
def run_demo():
"""
Run demo on images in folder "images"
"""
path = os.path.abspath("../images")
image_list = os.listdir(path)
for image_name in image_list:
image_path = os.path.join(path, image_name)
print("-----------------------------------------------")
print("Path:", image_path)
image = image_load(image_path)
detect_data = detection(image_path)
if len(detect_data) > 0:
draw_boxes(image,
detect_data[:, 0:4],
detect_data[:, 4],
detect_data[:, 5],
red=255)
show_image(image, False)
print(detect_data)
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))
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))
train_data[-1].append(float(info[i]))
with open("binMNIST_data/targetdigit_trn.csv") as f:
lines = f.readlines()
for line in lines:
train_label.append(int(line))
return train_data, train_label
def get_test_data():
test_data = []
test_label = []
index = 0
with open("binMNIST_data/bindigit_tst.csv") as f:
lines = f.readlines()
for line in lines:
test_data.append([])
info = line.split(",")
for i in range(784):
test_data[-1].append(float(info[i]))
with open("binMNIST_data/targetdigit_tst.csv") as f:
lines = f.readlines()
for line in lines:
test_label.append(int(line))
return test_data, test_label
if __name__ == "__main__":
x, y = get_train_data()
x1, y1 = get_test_data()
image.show_image(x[0])
print y[0]
