OpenCV

问题 I want to try create my own .xml file for my graduation project with this reference. But I have a problem which stage 6 doesn't work.It gives error such as: Traceback (most recent call last): File "./tools/mergevec.py", line 170, in <module> merge_vec_files(vec_directory, output_filename) File "./tools/mergevec.py", line 120, in merge_vec_files val = struct.unpack('<iihh', content[:12]) TypeError: a bytes-like object is required, not 'str' I have found a solution which says find 0 size vector

问题 I am developing a microservice to analyze an image uploaded to an S3 AWS Bucket. I am using Serverless framework. I am using virtualenv to install the dependencies with PIP and serverless-python-requirements plugin to deploy these dependencies to the Lambda function. However I am having an error when I deploy the microservice because of a missing .so file. The error I get is Unable to import module 'handlers.image': libgthread-2.0.so.0: cannot open shared object file: No such file My

问题 I am developing a microservice to analyze an image uploaded to an S3 AWS Bucket. I am using Serverless framework. I am using virtualenv to install the dependencies with PIP and serverless-python-requirements plugin to deploy these dependencies to the Lambda function. However I am having an error when I deploy the microservice because of a missing .so file. The error I get is Unable to import module 'handlers.image': libgthread-2.0.so.0: cannot open shared object file: No such file My

问题 What is My Issue? I have generated depth maps from monocular images using DenseDepth. Some of my results are below. I need help masking the darkest shades/ the darkest value of greys in a given range in the depth map. I would like to be able to give two hex values ie. #6E6E6E and #000000 and for the mask to select all the values in-between and then generate a black and white mask. What Have I Tried? After some research I came across this here: https://medium.com/@offsouza/segmentando-objetos

问题 What is My Issue? I have generated depth maps from monocular images using DenseDepth. Some of my results are below. I need help masking the darkest shades/ the darkest value of greys in a given range in the depth map. I would like to be able to give two hex values ie. #6E6E6E and #000000 and for the mask to select all the values in-between and then generate a black and white mask. What Have I Tried? After some research I came across this here: https://medium.com/@offsouza/segmentando-objetos

问题 I'm trying with the code from link below to blur faces in images: How to use opencv (python) to blur faces? image = cv2.imread('45.jpg') result_image = image.copy() # Specify the trained cascade classifier face_cascade_name = "‪C:/Users/User/Desktop/haarcascade_frontalface_alt.xml" # Create a cascade classifier face_cascade = cv2.CascadeClassifier() # Load the specified classifier face_cascade.load(face_cascade_name) #Preprocess the image grayimg = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

问题 I am making a mask using cv2.inRange(), which accepts an image, a lower bound, and an upper bound. The mask is working, but I want to return something like True/False or print('color present') if the color between the ranges is present. Here is some sample code: from cv2 import cv2 import numpy as np img = cv2.imread('test_img.jpg', cv2.COLOR_RGB2HSV) lower_range = np.array([0, 0, 0]) upper_range = np.array([100, 100, 100]) mask = cv2.inRange(img_hsv, lower_range, upper_range) #this is where

问题 I am making a mask using cv2.inRange(), which accepts an image, a lower bound, and an upper bound. The mask is working, but I want to return something like True/False or print('color present') if the color between the ranges is present. Here is some sample code: from cv2 import cv2 import numpy as np img = cv2.imread('test_img.jpg', cv2.COLOR_RGB2HSV) lower_range = np.array([0, 0, 0]) upper_range = np.array([100, 100, 100]) mask = cv2.inRange(img_hsv, lower_range, upper_range) #this is where

问题 I'm working on an Image Processing Algorithm that involves placing a mask on an image and hiding certain regions as follows, Image 1 Image 1 Reduced Visually Image 1 has undergone a reduction of about 50%. Some of the images I work with also end up having isolated regions like the one below. To compute reduction in the image I used the following code to calculate the increase in black pixels, sought = [0,0,0] black1 = np.count_nonzero(np.all(Image1==sought,axis=2)) #Black pixels in Image 1

问题 I am hiding an image inside another image (Image Steganography) by using python 3.6.8 with opencv 4.4.0.44. I am on windows 10 machine. The algorithm I am using is as follows: I have defined a mask with zeros at the last two lowest significant bits. Then I use this mask and "bitwise and" it to make the last two bits of every pixel in the base image to zero. There are two images, one is base image which accommodates the second image (hidden image). I have made sure the size of the hidden image