# Convert the black (for background) to white -> important to make a good overlapping 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). # Convert the white color (for blobs) to magenta Mask = Image.open(mask_folder+"/"+filename+".png").convert('RGB') # 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): 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. What I am doing wrong? Is there any straight way? I am coming from a Matlab environment and I am quite new to Python. VEED’s online video editor lets you add overlays to your videos in just one click. Plt.pcolormesh(x, y, Image2_mask,cmap='jet') Plt.axes().set_aspect('equal', 'datalim') Image2_mask = ma.masked_array(Image2,mask) The first one is a 512x512 NumPy array (from a CT image).
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