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DEMO_straightening.py 1.87 KiB
import algorithm.straighten_with_dlc as straighten
# CROPPING IMAGE
import cv2
import os
import matplotlib.pyplot as plt
from path_constants import abs_path_dlc_config
from path_constants import abs_path_temp_images
import time
def test():
cur_dir = os.getcwd()
image_to_predict = "notwork.png"
print(abs_path_dlc_config)
print(abs_path_temp_images)
print(image_to_predict)
config = os.path.abspath(abs_path_dlc_config)
os_directory_path = os.path.abspath(abs_path_temp_images)
image_type = image_to_predict[-4:]
img_directory = os_directory_path + '/' + image_to_predict
smallpath = os_directory_path + '/' + 'small' + image_to_predict
print(img_directory)
# reading image:
img = cv2.imread(img_directory)
# You will have to convert the color if you use OpenCV.
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
print("starting in 10s")
time.sleep(10)
print("Waking up")
str_image, img, points, shoulder_points, _ = straighten.straighten(image = img)
if str_image is not None:
str_image = cv2.cvtColor(str_image, cv2.COLOR_BGR2RGB)
cv2.imwrite(abs_path_temp_images + '/' + image_to_predict[0:-4] + '_str.png', str_image)
# data points
implot = plt.imshow(img)
print(points[0])
# put a blue dot at (10, 20)
plt.scatter(points[0][0], points[0][1], c='b', s=40, )
plt.scatter(points[1][0], points[1][1], c='r', s=40, )
plt.scatter(points[2][0], points[2][1], c='g', s=40, )
plt.scatter(points[3][0], points[3][1], c='y', s=40, )
plt.scatter(shoulder_points[0][0], shoulder_points[0][1], c='y', s=40, )
plt.scatter(shoulder_points[1][0], shoulder_points[1][1], c='y', s=40, )
plt.savefig(abs_path_temp_images + '/' + image_to_predict[0:-4] + '_points.png')
print("done in 10 s (so you can CHECK GPU USAGE)")
time.sleep(10)