I'm new to Python. I'm using Glob to Batch Process multiple image files. When I run my code, it processes and saves all image files as it should, but only one image file is affected by my code all other image files are untouched by my code. I need all images to be affected by my code. When I run my code on the two Checker Board image files, only one image file is affected the other image file is untouched by my code as shown in the images.
I tried researching more to find a solution, but I couldn't find one here is my code.
Thanks in advance,
import numpy as np
import cv2
import os
import glob
from skimage import img_as_ubyte
image_list = []
path = "opencv/imgs/*.*"
for file in glob.glob(path):
print(file)
img = cv2.imread(file)
a = cv2.imread(file)
image_list.append(img)
print(a)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,200,apertureSize=3)
img_blur = cv2.GaussianBlur(gray, (3,5), 2)
edges = cv2.Canny(image=img_blur, threshold1=25, threshold2=50) # Canny Edge Detection
# Apply HoughLinesP method to
# to directly obtain line end points
lines_list =[]
lines = cv2.HoughLinesP(
edges, # Input edge image
1, # Distance resolution in pixels
np.pi/2, # Angle resolution in radians
threshold=225, # Min number of votes for valid line
minLineLength=60, # Min allowed length of line
maxLineGap=400) # Max allowed gap between line for joining them
# Iterate over points
for points in lines:
# Extracted points nested in the list
x0,y1,x0,y2=points[0]
# Draw the lines joing the points
# On the original image
cv2.line(img,(x0,y1),(x0,y2),(0,255,0),4)
# Maintain a simples lookup list for points
lines_list.append([(x0,y1),(x0,y2)])
image_list = np.array(image_list)
# Save the result image
img_number = 1
for image in range(image_list.shape[0]):
input_img = image_list[image,:,:]
lines_image = img_as_ubyte(input_img)
cv2.imwrite(path+str(img_number)+".jpg", lines_image)
img_number +=1
All your problem it because you have wrong indentations. You run edge for every image (because it is still inside for-loop) but you run HoughLinesP outside for-loop so it is executed for only one image.
And I don't understand why later you use other another for-loop.
You should save current image in first loop and this loop will go to the beginning to process next image
Something like this:
import glob
import cv2
folder = "opencv/imgs"
path = f"{folder}/*.*"
for index, file in enumerate(glob.glob(path), 1):
print(index, 'file:', file)
# read only one file
img = cv2.imread(file)
print(img)
# process only one file
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray, 50, 200, apertureSize=3)
img_blur = cv2.GaussianBlur(gray, (3, 5), 2)
edges = cv2.Canny(image=img_blur, threshold1=25, threshold2=50) # Canny Edge Detection
# Apply HoughLinesP method to
# to directly obtain line end points
lines = cv2.HoughLinesP(
edges, # Input edge image
1, # Distance resolution in pixels
np.pi/2, # Angle resolution in radians
threshold=225, # Min number of votes for valid line
minLineLength=60, # Min allowed length of line
maxLineGap=400) # Max allowed gap between line for joining them
# Iterate over points
lines_list = []
for points in lines:
# Extracted points nested in the list
x0, y1, x0, y2 = points[0]
# Draw the lines joing the points
# On the original image
cv2.line(img, (x0, y1), (x0, y2), (0, 255, 0), 4)
# Maintain a simples lookup list for points ???
lines_list.append([(x0,y1),(x0,y2)])
# write only one file
cv2.imwrite(f"{folder}/{index}.jpg", img)
# end of current loop - go back to the beginning to work with next image
To make it more visible you could create function which gets one filename and it makes all calculation for one image, and it saves one image. And run this function in for-loop.
import glob
import cv2
def process_one_file(index, file, target_folder):
print(index, 'file:', file)
# read only one file
img = cv2.imread(file)
print(img)
# process only one file
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray, 50, 200, apertureSize=3)
img_blur = cv2.GaussianBlur(gray, (3, 5), 2)
edges = cv2.Canny(image=img_blur, threshold1=25, threshold2=50) # Canny Edge Detection
# Apply HoughLinesP method to
# to directly obtain line end points
lines = cv2.HoughLinesP(
edges, # Input edge image
1, # Distance resolution in pixels
np.pi/2, # Angle resolution in radians
threshold=225, # Min number of votes for valid line
minLineLength=60, # Min allowed length of line
maxLineGap=400) # Max allowed gap between line for joining them
# Iterate over points
lines_list = []
for points in lines:
# Extracted points nested in the list
x0, y1, x0, y2 = points[0]
# Draw the lines joing the points
# On the original image
cv2.line(img, (x0, y1), (x0, y2), (0, 255, 0), 4)
# Maintain a simples lookup list for points ???
lines_list.append([(x0,y1),(x0,y2)])
# write only one file
cv2.imwrite(f"{target_folder}/{index}.jpg", img)
# exit function
# --- main ---
folder = "opencv/imgs"
path = f"{folder}/*.*"
for index, file in enumerate(glob.glob(path), 1):
process_one_file(index, file, folder)
# end of current loop - go back to the beginning to work with next image