kandi X-RAY | opencv-python Summary
kandi X-RAY | opencv-python Summary
Pre-built CPU-only OpenCV packages for Python. Check the manual build section if you wish to compile the bindings from source to enable additional modules such as CUDA.
Top functions reviewed by kandi - BETA
opencv-python Key Features
opencv-python Examples and Code Snippets
import cv2 from imutils import contours # Load image, grayscale, Gaussian blur, Otsu's threshold image = cv2.imread('1.png') original = image.copy() gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) blur = cv2.GaussianBlur(gray, (7,7), 0) th
import cv2 import numpy as np img = cv2.imread('scanned_image.png', cv2.IMREAD_GRAYSCALE) # Read image as grayscale thesh = cv2.threshold(img, 0, 255, cv2.THRESH_OTSU + cv2.THRESH_BINARY_INV) # Apply automatic thresholding with inve
import cv2 import numpy as np # read image img = cv2.imread('form_with_label.jpg') # threshold on yellow lower=(0,200,200) upper=(100,255,255) thresh = cv2.inRange(img, lower, upper) # apply dilate morphology kernel = np.ones((9,9), np.
# import the necessary packages import argparse import cv2 # construct the argument parser and parse the arguments ap = argparse.ArgumentParser() ap.add_argument("-i", "--image", type=str, default="pca8e.png", help="path to input image
import cv2 import numpy as np # Load image, grayscale, Gaussian blur, Otsu's threshold image = cv2.imread("1.png") mask = np.zeros(image.shape, dtype=np.uint8) original = image.copy() gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) blur =
import cv2 import pytesseract img = cv2.imread('gamepictures/text.png') # Load the image img = img[98:190,6:149,:] img = cv2.cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # convert to grey img = cv2.GaussianBlur(img, (5, 5), 3) img = cv2.adapti
#!/usr/bin/env python import itertools as its import sys import time import cv2 import numpy as np def draw_img_orig(arr_in, arr_out, *args): factor = round(arr_out.shape / arr_in.shape) factor_2 = factor // 2 it = np
import cv2 import numpy as np # load image as grayscale img = cv2.imread('Diabetic-Retinopathy_G_RM_151064169.jpg') gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # threshold input image mask = cv2.threshold(gray, 10, 255, cv2.THRESH_BINA
import cv2 import numpy as np # load image img = cv2.imread('black_circle.png') # convert to grayscale gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # threshold threshold = cv2.threshold(gray,128,255,cv2.THRESH_BINARY) # invert so ci
import cv2 import numpy as np image = cv2.imread('tulips.jpg') # Fill the black background with white color #cv2.floodFill(image, None, seedPoint=(0, 0), newVal=(0, 0, 255), loDiff=(2, 2, 2), upDiff=(2, 2, 2)) # Not working! hsv_img = c
Trending Discussions on opencv-python
Hello stackoverflow people:) I'm trying to masking many image from two different path, but I don't have an idea to do that. This an example for just two images and what I've do so far...
ANSWERAnswered 2022-Mar-31 at 04:06
Hope it will work for you !
I have pretrained model for object detection (Google Colab + TensorFlow) inside Google Colab and I run it two-three times per week for new images I have and everything was fine for the last year till this week. Now when I try to run model I have this message:...
ANSWERAnswered 2022-Feb-07 at 09:19
It happened the same to me last friday. I think it has something to do with Cuda instalation in Google Colab but I don't know exactly the reason
I have tried the similar problems' solutions on here but none seem to work. It seems that I get a memory error when installing tensorflow from requirements.txt. Does anyone know of a workaround? I believe that installing with --no-cache-dir would fix it but I can't figure out how to get EB to do that. Thank you.
ANSWERAnswered 2022-Feb-05 at 22:37
The error says
MemoryError. You must upgrade your ec2 instance to something with more memory.
tensorflow is very memory hungry application.
Error while installing manimce, I have been trying to install manimce library on windows subsystem for linux and after running...
ANSWERAnswered 2022-Jan-28 at 02:24
apt-get install sox ffmpeg libcairo2 libcairo2-dev apt-get install texlive-full pip3 install manimlib # or pip install manimlib
I am trying to write an object detection + text-to-speech code to detect objects and produce a voice output on the raspberry pi 4. However, as of right now, I am trying to write a simple python script that incorporates both elements into a single .py file and preferably as a function. I will then run this script on the raspberry pi. I want to give credit to Murtaza's Workshop "Object Detection OpenCV Python | Easy and Fast (2020)" and https://pypi.org/project/pyttsx3/ for the Text to speech documentation for pyttsx3. I have attached the code below. I have tried running the program and I always keep getting errors with the Text to speech code (commented lines 33-36 for reference). I believe it is some looping error but I just can't seem to get the program to run continuously. For instance, if I run the code without the TTS part, it works fine. Otherwise, it runs for perhaps 3-5 seconds and suddenly stops. I am a beginner but highly passionate in computer vision, and any help is appreciated!...
ANSWERAnswered 2021-Dec-28 at 16:46
I installed pyttsx3 using the two commands in the terminal on the Raspberry Pi:
- sudo apt update && sudo apt install espeak ffmpeg libespeak1
- pip install pyttsx3
I followed the video youtube.com/watch?v=AWhDDl-7Iis&ab_channel=AiPhile to install pyttsx3. My functional code should also be listed above. My question should be resolved but hopefully useful to anyone looking to write a similar program. I have made minor tweaks to my code.
I am trying to run the training of stylegan2-pytorch on a remote system. The remote system has gcc (9.3.0) installed on it. I'm using conda env that has the following installed (cudatoolkit=10.2, torch=1.5.0+, and ninja=1.8.2, gcc_linux-64=7.5.0). I encounter the following error:...
ANSWERAnswered 2021-Dec-12 at 16:12
Just to share, not sure it will help you. However it shows that in standard conditions it is possible to use the
gcc as described in the documentation instead of the system
I'm working on CI for my Python + Django project. I have to use the
python:3.9-alpine image. A weird error is popping in my CI pipelines:
ANSWERAnswered 2021-Dec-05 at 17:35
What is the reason of my error?
Did you read my previous answer to a similar question of yours? The last part warns about certain combinations of Alpine + Python and this seems to be happening right now.
I tried to replace psycopg2 with psycopg2-binary but have the same error
The problem here might be a python library that has dependencies on
gcc, which is not shipped on alpine by default.
Try replacing this:
I am working on CI/CD for my python/django project in gitlab.
I have an error -- Gitlab CI: Failed building wheel for opencv-python
Full gitlab ci log -- https://pastebin.com/pZdZ6ws2
I have an error on the
ANSWERAnswered 2021-Dec-04 at 23:03
In your logs, we can see the following error:
I am trying to install the Tensorflow Object Detection API on a Google Colab and the part that installs the API, shown below, takes a very long time to execute (in excess of one hour) and eventually fails to install....
ANSWERAnswered 2021-Nov-19 at 00:16
I have solved this problem with
i have an import problem when executing my code:...
ANSWERAnswered 2021-Oct-06 at 20:27
You're using outdated imports for
tf.keras. Layers can now be imported directly from
No vulnerabilities reported
If you have previous/other manually installed (= not installed via pip) version of OpenCV installed (e.g. cv2 module in the root of Python's site-packages), remove it before installation to avoid conflicts.
Make sure that your pip version is up-to-date (19.3 is the minimum supported version): pip install --upgrade pip. Check version with pip -V. For example Linux distributions ship usually with very old pip versions which cause a lot of unexpected problems especially with the manylinux format.
Select the correct package for your environment: There are four different packages (see options 1, 2, 3 and 4 below) and you should SELECT ONLY ONE OF THEM. Do not install multiple different packages in the same environment. There is no plugin architecture: all the packages use the same namespace (cv2). If you installed multiple different packages in the same environment, uninstall them all with pip uninstall and reinstall only one package. a. Packages for standard desktop environments (Windows, macOS, almost any GNU/Linux distribution) Option 1 - Main modules package: pip install opencv-python Option 2 - Full package (contains both main modules and contrib/extra modules): pip install opencv-contrib-python (check contrib/extra modules listing from OpenCV documentation) b. Packages for server (headless) environments (such as Docker, cloud environments etc.), no GUI library dependencies These packages are smaller than the two other packages above because they do not contain any GUI functionality (not compiled with Qt / other GUI components). This means that the packages avoid a heavy dependency chain to X11 libraries and you will have for example smaller Docker images as a result. You should always use these packages if you do not use cv2.imshow et al. or you are using some other package (such as PyQt) than OpenCV to create your GUI. Option 3 - Headless main modules package: pip install opencv-python-headless Option 4 - Headless full package (contains both main modules and contrib/extra modules): pip install opencv-contrib-python-headless (check contrib/extra modules listing from OpenCV documentation)
Import the package: import cv2 All packages contain Haar cascade files. cv2.data.haarcascades can be used as a shortcut to the data folder. For example: cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")
Read OpenCV documentation
Before opening a new issue, read the FAQ below and have a look at the other issues which are already open.
The project is structured like a normal Python package with a standard setup.py file. The build process for a single entry in the build matrices is as follows (see for example appveyor.yml file):. Steps 1--4 are handled by pip wheel.
In Linux and MacOS build: get OpenCV's optional C dependencies that we compile against
Checkout repository and submodules OpenCV is included as submodule and the version is updated manually by maintainers when a new OpenCV release has been made Contrib modules are also included as a submodule
Find OpenCV version from the sources
Build OpenCV tests are disabled, otherwise build time increases too much there are 4 build matrix entries for each build combination: with and without contrib modules, with and without GUI (headless) Linux builds run in manylinux Docker containers (CentOS 5) source distributions are separate entries in the build matrix
Rearrange OpenCV's build result, add our custom files and generate wheel
Linux and macOS wheels are transformed with auditwheel and delocate, correspondingly
Install the generated wheel
Test that Python can import the library and run some sanity checks
Use twine to upload the generated wheel to PyPI (only in release builds)
CI_BUILD. Set to 1 to emulate the CI environment build behaviour. Used only in CI builds to force certain build flags on in setup.py. Do not use this unless you know what you are doing.
ENABLE_CONTRIB and ENABLE_HEADLESS. Set to 1 to build the contrib and/or headless version
ENABLE_JAVA, Set to 1 to enable the Java client build. This is disabled by default.
CMAKE_ARGS. Additional arguments for OpenCV's CMake invocation. You can use this to make a custom build.
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