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a-cv-imwrite-imread-plus-0.11


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توضیحات

Less trouble reading/writing images with OpenCV (from url/path/buffer/base64...)
ویژگی مقدار
سیستم عامل -
نام فایل a-cv-imwrite-imread-plus-0.11
نام a-cv-imwrite-imread-plus
نسخه کتابخانه 0.11
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Johannes Fischer
ایمیل نویسنده <aulasparticularesdealemaosp@gmail.com>
آدرس صفحه اصلی https://github.com/hansalemaos/a_cv_imwrite_imread_plus
آدرس اینترنتی https://pypi.org/project/a-cv-imwrite-imread-plus/
مجوز MIT
# Less trouble reading/writing images with OpenCV ```python $pip install a-cv-imwrite-imread-plus from a_cv_imwrite_imread_plus import add_imwrite_plus_imread_plus_to_cv2 add_imwrite_plus_imread_plus_to_cv2() cv2.imwrite_plus("f:\\ö\\ö\\ö\\öädssdzß.jpg", base64img2cv) #or: from a_cv_imwrite_imread_plus import save_cv_image save_cv_image("f:\\ö\\ö\\ö\\öädssdzß.jpg", base64img2cv) Parameters: filepath:str folders will be created if they don't exist image:np.ndarray image as np Returns: filepath:str ``` ```python from a_cv_imwrite_imread_plus import add_imwrite_plus_imread_plus_to_cv2 add_imwrite_plus_imread_plus_to_cv2() import base64 from PIL import Image import cv2 #Base64 base64img = r"data:image/png;base64,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" base64img2 = r"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" base64imgcv = cv2.imread_plus(base64img) base64img2cv = cv2.imread_plus(base64img2) base64imgcv = cv2.imread_plus(base64img, channels_in_output=4) base64img2cv = cv2.imread_plus(base64img2, channels_in_output=4) base64imgcv = cv2.imread_plus(base64img, channels_in_output=2) base64img2cv = cv2.imread_plus(base64img2, channels_in_output=2) #urls pininterestlogo = "https://camo.githubusercontent.com/7f81f312b05694ccc8cd29e3c3466945ff8e73a13320d3fd0f90c6915bbb4ffb/68747470733a2f2f63646e2e6a7364656c6976722e6e65742f67682f646d68656e647269636b732f7369676e61747572652d736f6369616c2d69636f6e732f69636f6e732f726f756e642d666c61742d66696c6c65642f353070782f70696e7465726573742e706e67" linkcv1 = cv2.imread_plus(pininterestlogo) linkcv2 = cv2.imread_plus(pininterestlogo, channels_in_output=4) linkcv3 = cv2.imread_plus(pininterestlogo, channels_in_output=2) linkcv4 = cv2.imread_plus(pininterestlogo, channels_in_output=3) #bytes/raw data byteimage = base64.b64decode(base64img2) byteimage1 = cv2.imread_plus(byteimage) byteimage2 = cv2.imread_plus(byteimage, channels_in_output=4) byteimage3 = cv2.imread_plus(byteimage, channels_in_output=2) byteimage4 = cv2.imread_plus(byteimage, channels_in_output=3) #PIL pilimage = Image.fromarray(byteimage2) pilimage1 = cv2.imread_plus(pilimage) pilimage2 = cv2.imread_plus(pilimage, channels_in_output=4) pilimage3 = cv2.imread_plus(pilimage, channels_in_output=2) pilimage4 = cv2.imread_plus(pilimage, channels_in_output=3) #float images to np.uint8 floatimage = pilimage4.astype(float) floatimage1 = cv2.imread_plus(floatimage) floatimage2 = cv2.imread_plus(floatimage, channels_in_output=4) floatimage3 = cv2.imread_plus(floatimage, channels_in_output=2) floatimage4 = cv2.imread_plus(floatimage, channels_in_output=3) #filepath filepath = "c:\\testestestes.png" pilimage.save(filepath) filepath1 = cv2.imread_plus(filepath, bgr_to_rgb=True) filepath2 = cv2.imread_plus(filepath, channels_in_output=4, bgr_to_rgb=True) filepath3 = cv2.imread_plus(filepath, channels_in_output=2, bgr_to_rgb=True) filepath4 = cv2.imread_plus(filepath, channels_in_output=3, bgr_to_rgb=True) #or: from a_cv_imwrite_imread_plus import open_image_in_cv #Base64 base64img = r"data:image/png;base64,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" base64img2 = r"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" base64imgcv = open_image_in_cv(base64img) base64img2cv = open_image_in_cv(base64img2) base64imgcv = open_image_in_cv(base64img, channels_in_output=4) base64img2cv = open_image_in_cv(base64img2, channels_in_output=4) base64imgcv = open_image_in_cv(base64img, channels_in_output=2) base64img2cv = open_image_in_cv(base64img2, channels_in_output=2) #urls pininterestlogo = "https://camo.githubusercontent.com/7f81f312b05694ccc8cd29e3c3466945ff8e73a13320d3fd0f90c6915bbb4ffb/68747470733a2f2f63646e2e6a7364656c6976722e6e65742f67682f646d68656e647269636b732f7369676e61747572652d736f6369616c2d69636f6e732f69636f6e732f726f756e642d666c61742d66696c6c65642f353070782f70696e7465726573742e706e67" linkcv1 = open_image_in_cv(pininterestlogo) linkcv2 = open_image_in_cv(pininterestlogo, channels_in_output=4) linkcv3 = open_image_in_cv(pininterestlogo, channels_in_output=2) linkcv4 = open_image_in_cv(pininterestlogo, channels_in_output=3) #bytes/raw data byteimage = base64.b64decode(base64img2) byteimage1 = open_image_in_cv(byteimage) byteimage2 = open_image_in_cv(byteimage, channels_in_output=4) byteimage3 = open_image_in_cv(byteimage, channels_in_output=2) byteimage4 = open_image_in_cv(byteimage, channels_in_output=3) #PIL pilimage = Image.fromarray(byteimage2) pilimage1 = open_image_in_cv(pilimage) pilimage2 = open_image_in_cv(pilimage, channels_in_output=4) pilimage3 = open_image_in_cv(pilimage, channels_in_output=2) pilimage4 = open_image_in_cv(pilimage, channels_in_output=3) #float images to np.uint8 floatimage = pilimage4.astype(float) floatimage1 = open_image_in_cv(floatimage) floatimage2 = open_image_in_cv(floatimage, channels_in_output=4) floatimage3 = open_image_in_cv(floatimage, channels_in_output=2) floatimage4 = open_image_in_cv(floatimage, channels_in_output=3) #filepath filepath = "c:\\testestestes.png" pilimage.save(filepath) filepath1 = open_image_in_cv(filepath, bgr_to_rgb=True) filepath2 = open_image_in_cv(filepath, channels_in_output=4, bgr_to_rgb=True) filepath3 = open_image_in_cv(filepath, channels_in_output=2, bgr_to_rgb=True) filepath4 = open_image_in_cv(filepath, channels_in_output=3, bgr_to_rgb=True) from a_cv2_imshow_thread import add_imshow_thread_to_cv2 add_imshow_thread_to_cv2() cv2.imshow_thread( [ base64imgcv, base64img2cv, linkcv1, linkcv2, linkcv3, linkcv4, byteimage1, byteimage2, byteimage3, byteimage4, pilimage1, pilimage2, pilimage3, pilimage4, floatimage1, floatimage2, floatimage3, floatimage4, filepath1, filepath2, filepath3, filepath4, ] ) Parameters: image:Any Can be URL, bytes, base64, file path, np.ndarray, PIL channels_in_output:Union[int,None] None (original image won't be changed) 2 (GRAY) 3 (BGR) 4 (BGRA) (default=None) bgr_to_rgb:bool=False Converts BGRA to RGBA / BGR to RGB Returns: image:np.ndarray (Always as np.uint8) ```


نیازمندی

مقدار نام
- numpy
- opencv-python
- requests
- touchtouch


نحوه نصب


نصب پکیج whl a-cv-imwrite-imread-plus-0.11:

    pip install a-cv-imwrite-imread-plus-0.11.whl


نصب پکیج tar.gz a-cv-imwrite-imread-plus-0.11:

    pip install a-cv-imwrite-imread-plus-0.11.tar.gz