def rotate_to_horizontal(self, image):
image = self.correct_dimensions(image, 1600)
if self.determine_tray_orientation(image) == -1:
image = self.rotate_image(image, -45)
elif self.determine_tray_orientation(image) == 1:
image = self.rotate_image(image, 45)
return ImageProcUtil.crop_out_blackv2(image)
def find_dot_locations(self, imagearray):
imagearraytransformed,cent=ImageProcUtil.threshold_dots_withcenter(imagearray)
#print('hi')
#plt.imshow(imagearraytransformed)
#plt.show()
imagearraytransformed=self.noise_remover.remove_noise(imagearraytransformed)
self.cent=cent
#print('hi2')
#plt.imshow(imagearraytransformed)
#plt.show()
img_gray=cv2.cvtColor(imagearraytransformed, cv2.COLOR_BGR2GRAY)
ret,thresholded=cv2.threshold(img_gray,1,255,cv2.THRESH_BINARY)
#dev,thresholded=pcv.fill(thresholded, thresholded, 5, 0)
#cv2.imshow("hi",thresholded)
###cv2.waitKey(0)
#cv2.destroyAllWindows()
w1, contours, w2 = cv2.findContours(thresholded, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
print(len(contours))
withcont=cv2.drawContours(imagearraytransformed, contours, -1, (0,255,0),1)
#plt.imshow(withcont)
#plt.show()
centers=self.find_centers_of_dots(contours)
centersfinal=list()
for i in centers:
centersfinal.append(tuple([i[0]+self.cent[1], i[1]+self.cent[0]]))
withcont=cv2.circle(imagearray, tuple([i[0]+self.cent[1], i[1]+self.cent[0]]), 5,(255,0,0))
withcont=cv2.circle(withcont, tuple([self.cent[0], self.cent[1]]), 5, (0,0,255))
#plt.imshow(withcont)
#plt.show()
return centersfinal
def determine_dot_code_order(self, image):
trays = self.shelf_segmenter.split(image)
tray = trays[0]
tray, _center = ImageProcUtil.threshold_dots3_slack(tray)
tray = self.noise_removal.remove_noise(tray)
tray_grey = cv2.cvtColor(tray, cv2.COLOR_BGR2GRAY)
thresholded_tray_grey = cv2.threshold(tray_grey, 1, 255,
cv2.THRESH_BINARY)[1]
w1, contours, w2 = cv2.findContours(thresholded_tray_grey,
cv2.RETR_TREE,
cv2.CHAIN_APPROX_NONE)
big_dot = max(contours, key=cv2.contourArea)
moments = cv2.moments(big_dot)
ycoords = int(moments['m10'] / moments['m00'])
xcoords = int(moments['m01'] / moments['m00'])
if ycoords <= int(tray.shape[1] / 2):
return True
else:
return False
def process_tray(self, tray_img_path,section_types):
"""Return list of tray objects"""
#cropped=ImageProcUtil.crop_out_black(tray_img_path)
#plt.imshow(cropped)
#plt.show()
tray_counter=0
tray_struct=list()
all_errors = list()
trays=self.shelf_segmenter.split(cv2.imread(tray_img_path))
errors=0
for i in trays:
#plt.imshow(i)
#plt.show()
try:
#plt.imshow(i)
#splt.show()
pass
except:
continue
#i=self.color_enhancement(i,0.4)
#plt.imshow(i)
#plt.show()]
try:
#plt.imshow(i)
#plt.show()
cleaned,centers_adjustment=ImageProcUtil.threshold_dots3_slack(i)
cleaned = self.noise_removal.remove_noise2(cleaned)
# cv2.imshow("hi",cleaned)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
except Exception as e:
# cv2.imshow('hi',i)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
tray_counter += 1
#print("errors",e)
print(e)
continue
def add_to_registry(self, tray_img_path, section_types):
os.chdir('/Users/gghosal/Desktop/gaurav/photos')
tray_counter = 0
tray_struct = list()
trays = self.shelf_segmenter.split(cv2.imread(tray_img_path))
for i in trays:
cleaned = ImageProcUtil.threshold_dots(i)
cleaned = self.noise_removal.remove_noise(cleaned)
pots = self.potsegmenter.split_half_trays(i)
potsfinal = list()
for q in pots:
if bool((q.shape[0] >= 100) and (q.shape[1] >= 100)):
potsfinal.append(q)
pots = potsfinal
try:
tray_id = self.dotcodereader.read_image2(cleaned)
cv2.imshow("hi", i)
k = cv2.waitKey()
a = input("Correct Sequence?")
if not a == "c":
dot_description = a.split(",")
description = str()
for dotqualifier in dot_description:
description += dotqualifier
updated_dot_code_id = self.dotcodereader.translator.get(
description, "Error!Try again")
print("Corrected: ", updated_dot_code_id)
tray_id = updated_dot_code_id
tray_struct.append(
tuple(tray_id, section_types[tray_counter % 3]))
tray_counter += 1
except:
pass
self.registry[
os.path.split(tray_img_path)[1].split("_")[1] + "_" +
os.path.split(tray_img_path)[1].split("_")[2] +
os.path.split(tray_img_path)[1].split("_")[3]] = tray_struct
#cleaned_grey=cv2.cvtColor(cleaned, cv2.COLOR_RGB2HSV)
#cleaned_grey=cleaned_grey
#cleaned_thresh=cv2.inRange(cleaned_grey,np.array([0,0,150]),np.array([255,255,255]))
#cleaned=cv2.bitwise_and(cleaned, cleaned, mask=cleaned_thresh)
#kernel = np.ones((7,7),np.uint8)
#cleaned = cv2.morphologyEx(cleaned, cv2.MORPH_CLOSE,(31,31))
#kernel = np.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]])
#im = cv2.filter2D(cleaned, -1, kernel)
#cleaned=cv2.bitwise_and(cleaned, cleaned, mask=th3)
cleaned=ImageProcUtil.cvtcolor_bgr_rgb(cleaned)
#grey=cv2.cvtColor(cleaned, cv2.COLOR_BGR2GRAY)
#_,thresh=cv2.threshold(grey, 1,255, cv2.THRESH_BINARY)
#_,binarymask=cv2.threshold(grey, 80,255,cv2.THRESH_BINARY)
#cleaned=cv2.bitwise_and(cleaned, cleaned, mask=binarymask)
#binarymask=grey>binarymask
#print(binarymask)
## for i in range(binarymask.shape[0]):
## for p in range(binarymask.shape[1]):
## if binarymask[i][p]:
## binarymask[i][p]=255
## else:
## binarymask[i][p]=0
for i in list(
listdir_nohidden("/Users/gghosal/Desktop/gaurav_new_photos/Shelf3_1")):
os.chdir("/Users/gghosal/Desktop/gaurav_new_photos/Shelf3_1")
for j in shelf_segmenter.split(
apply_brightness_contrast(
cv2.imread('20131104_Shelf3_1900_1_masked.tif'),
brightness=0,
contrast=0)):
try:
#cleaned,_=ImageProcUtil.threshold_dots3(j)
#cleaned=noise_removal.remove_noise(cleaned)
cv2.imshow("hi", j)
cv2.waitKey(0)
cv2.destroyAllWindows()
cleaned2, _ = ImageProcUtil.threshold_dots3_slack(j)
cleaned2 = noise_removal.remove_noise(cleaned2)
## cleaned2grey=cv2.cvtColor(cleaned2, cv2.COLOR_BGR2GRAY)
## _,cleaned2thresh=cv2.threshold(cleaned2grey, 10, 255, cv2.THRESH_BINARY)
## #print(cleaned2thresh)
## w1,cnt,w2=cv2.findContours(cleaned2thresh, cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
## #cnt=cnt[1:]
## #cnt=cnt[0]
## realcnt=[]
## for c in cnt:
## #print(c)
## perimeter = cv2.arcLength(c, True)
## area = cv2.contourArea(c)
## circularity = 4*math.pi*(area/(perimeter*perimeter))
## print(circularity)
for contourtocheck in clusters1:
if not obj_hierarchy[contourtocheck][2] == -1:
if not cv2.contourArea(
contours[obj_hierarchy[contourtocheck][2]]) >= 20:
obj_hierarchy[contourtocheck][2] = -1
counter = 0
for foundcontour in clusters_i:
hierarchycontours = [obj_hierarchy[j][2] for j in foundcontour]
if not all([bool(j == -1) for j in hierarchycontours]):
dotQ.append(True)
else:
dotQ.append(False)
return dotQ
if __name__ == '__main__':
a = DotCodeReader("/Users/gghosal/Desktop/dotcodestranslated.dat", {
'red': 0,
"lightblue": 98,
"darkblue": 120,
"pink": 173,
"purple": 160
})
b = NoiseRemoval.NoiseRemoval()
FILE = "/Users/gghosal/Documents/GitHub/PlantTrayMeasuringPipeline/Figure_1.jpg"
print(
a.read_image2(
b.remove_noise(ImageProcUtil.threshold_dots(
pcv.readimage(FILE)[0]))))