Return cv2.addWeighted(np.array(img),0.4,np.array(mask_colored),0.3,0)įunction to change color of each pixel in a picture : def change_color(picture, width, height, ex_color, new_color):Ĭurrent_color = picture. # Convert the black (for background) to white -> important to make a good overlapping # Convert the white color (for blobs) to magenta You can also add color grading to change the general tone of your video. Add a bokeh effect, film burn, light leaks, VHS overlay, and more You can also add camera filters to achieve the look and feel that you want for your video. Mask = Image.open(mask_folder+"/"+filename+".png").convert('RGB') VEED’s online video editor lets you add overlays to your videos in just one click. # Import and convert the mask from binary to RGB Img = cv2.imread(img_folder+"/"+filename+".jpg") I can give you my function two overlap a picture and a mask of dataset : def get_overlapped_img(filename, img_folder, mask_folder): What I am doing wrong? Is there any straight way? I am coming from a Matlab environment and I am quite new to Python. Plt.pcolormesh(x, y, Image2_mask,cmap='jet') Plt.axes().set_aspect('equal', 'datalim') Click the 'Download' button to save photos as you like format. Modify the text, and change the color, size, background, or transparency. Click the one you like or directly drag it to your image. Image2_mask = ma.masked_array(Image2,mask) Click 'Open Image' to upload your picture which wants to add text. To do that I am trying to create a masked array. The second one is also a 512x512 NumPy array but I am just interested in the pixels where the value is larger than 0 (a functional image). The first one is a 512x512 NumPy array (from a CT image).
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