COCO Image Viewer | immersivelimit.com/tutorials/create-coco-annotations-from-scratch

COCO_Image_Viewer.ipynb

@madhavajay, I updated the gist with your suggested fix. Thanks again for the fix!

Hi @akTwelve, upon visualizing my own custom dataset I noticed that the masks of some instances did not get displayed while those of some did. This was due to segmentation_points being a numpy array, so sometimes the array when stringified looked like this '241, 5, 242, ..., 244, 5, 245]'. It can be avoided by adding:
segmentation_points = list (segmentation_points) after the following line of the function display_image in the notebook.
segmentation_points = np.multiply(segmentation_points, adjusted_ratio).astype(int).

Thanks for sharing!
I quickly added the option to visualize keypoints. I simply added the parameter in the display_image function:

def display_image(self, image_id, show_polys=True, show_bbox=True, show_crowds=True, show_keypoints=True, use_url=False):

and in the function body below the if show_bbox block I added:

if show_keypoints:
    for i, segm in enumerate(self.segmentations[image_id]):
        keypoints = segm.get('keypoints', None)
        if not keypoints is None:
            for k in range(0, segm.get('num_keypoints', 0)):
                x = keypoints[k * 3 + 0]
                y = keypoints[k * 3 + 1]
                visibility = keypoints[k * 3 + 2]
                html += '<circle cx="{}" cy="{}" r="3" fill="{}" />'.format(x, y, "red")

this will draw all keypoints using red svg circles, regardless of their visibility.

Thank you for sharing!

For photos with non-landscape orientation I had to add this to your code: https://stackoverflow.com/a/63798032/1616037