mask = cv2.blur(mask, (3, 3))
img_gray = image_processor.gray(img_raw)
# For possible future purposes
mask_canny_edge = image_processor.canny(mask)
img_canny_edge = image_processor.auto_canny(img_gray)
mask_weight = 1.0
combined_canny_edge = image_processor.combine_edges(
mask_canny_edge, mask_weight, img_canny_edge, (1 - mask_weight))
object_contour = image_processor.max_contour(combined_canny_edge)
if key == ord('q'):
cv2.destroyAllWindows()
motor.cleanUp()
quit()
try:
bounding_box = image_processor.bounding_box(object_contour)
except:
continue
cv2.drawContours(img_raw, object_contour, -1, (0, 255, 0), 3)
#print(bounding_box)
cv2.rectangle(img_raw, bounding_box[0], bounding_box[1], (0, 255, 0),
2)
# display stuff
cv2.imshow('canny', combined_canny_edge)
cv2.imshow('raw', img_raw)
OTL_cut_out = img_deleted_background[
bounding_box[0][1]:bounding_box[1][1],
bounding_box[0][0]:bounding_box[1][0], :]
cv2.imshow('cut_out', OTL_cut_out)
# Possibility to save images
if key == ord('s'):
from image_capture import ImageCapture
from image_processing import ImageProcessing
import cv2
import numpy as np
camera = ImageCapture()
#camera = cv2.VideoCapture(0)
processor = ImageProcessing()
while True:
img_raw = camera.capture()
img_cut = img_raw[:,
int(np.shape(img_raw)[1] * 1 /
5):int(np.shape(img_raw)[1] * 4 / 5), :]
img_gray = processor.gray(img_cut)
edge = processor.canny(img_gray)
contour = processor.max_contour(edge)
cv2.drawContours(img_cut, contour, -1, (0, 255, 0), 3)
bounding_box = processor.bounding_box(contour)
print(bounding_box)
#if bounding_box != -1:
# print("success!")
#else:
# print("failure!")
cv2.imshow('raw_image', img_raw)
cv2.imshow('cut_image', img_cut)
cv2.imshow('gray_image', img_gray)
cv2.imshow('canny_image', edge)
cv2.waitKey(20)
