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Add save the depth image results #30

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Add save the depth image results #30

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9 changes: 7 additions & 2 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -109,16 +109,21 @@ pip install -r requirements.txt
### Running

```bash
python run.py --encoder <vits | vitb | vitl> --img-path <img-directory | single-img | txt-file> --outdir <outdir>
python run.py --encoder <vits | vitb | vitl> --img-path <img-directory | single-img | txt-file> --outdir <outdir> [--save_depth_img]
```
For the ``img-path``, you can either 1) point it to an image directory storing all interested images, 2) point it to a single image, or 3) point it to a text file storing all image paths.

For example:
Example 1:
```bash
python run.py --encoder vitl --img-path assets/examples --outdir depth_visualization
```

Example 2:

If you just want to save the depth image results.
```bash
python run.py --encoder vitl --img-path assets/examples --outdir depth_visualization --save_depth_img
```
### Gradio demo

To use our gradio demo locally:
Expand Down
53 changes: 29 additions & 24 deletions run.py
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Expand Up @@ -16,7 +16,8 @@
parser.add_argument('--img-path', type=str)
parser.add_argument('--outdir', type=str, default='./vis_depth')
parser.add_argument('--encoder', type=str, default='vitl', choices=['vits', 'vitb', 'vitl'])

parser.add_argument('--save_depth_img', default=False, action='store_true')

args = parser.parse_args()

margin_width = 50
Expand Down Expand Up @@ -73,30 +74,34 @@
depth = depth_anything(image)

depth = F.interpolate(depth[None], (h, w), mode='bilinear', align_corners=False)[0, 0]
depth = (depth - depth.min()) / (depth.max() - depth.min()) * 255.0

depth = depth.cpu().numpy().astype(np.uint8)
depth_color = cv2.applyColorMap(depth, cv2.COLORMAP_INFERNO)


os.makedirs(args.outdir, exist_ok=True)
filename = os.path.basename(filename)

split_region = np.ones((raw_image.shape[0], margin_width, 3), dtype=np.uint8) * 255
combined_results = cv2.hconcat([raw_image, split_region, depth_color])

caption_space = np.ones((caption_height, combined_results.shape[1], 3), dtype=np.uint8) * 255
captions = ['Raw image', 'Depth Anything']
segment_width = w + margin_width
for i, caption in enumerate(captions):
# Calculate text size
text_size = cv2.getTextSize(caption, font, font_scale, font_thickness)[0]

# Calculate x-coordinate to center the text
text_x = int((segment_width * i) + (w - text_size[0]) / 2)
if args.save_depth_img:
cv2.imwrite(os.path.join(args.outdir, filename[:filename.find('.')] + '_img_depth.png'), depth.cpu().numpy().astype(np.uint16))
else:
depth = (depth - depth.min()) / (depth.max() - depth.min()) * 255.0
depth = depth.cpu().numpy().astype(np.uint8)
depth_color = cv2.applyColorMap(depth, cv2.COLORMAP_INFERNO)

split_region = np.ones((raw_image.shape[0], margin_width, 3), dtype=np.uint8) * 255
combined_results = cv2.hconcat([raw_image, split_region, depth_color])

caption_space = np.ones((caption_height, combined_results.shape[1], 3), dtype=np.uint8) * 255

# Add text caption
cv2.putText(caption_space, caption, (text_x, 40), font, font_scale, (0, 0, 0), font_thickness)

final_result = cv2.vconcat([caption_space, combined_results])

cv2.imwrite(os.path.join(args.outdir, filename[:filename.find('.')] + '_img_depth.png'), final_result)
captions = ['Raw image', 'Depth Anything']
segment_width = w + margin_width
for i, caption in enumerate(captions):
# Calculate text size
text_size = cv2.getTextSize(caption, font, font_scale, font_thickness)[0]

# Calculate x-coordinate to center the text
text_x = int((segment_width * i) + (w - text_size[0]) / 2)

# Add text caption
cv2.putText(caption_space, caption, (text_x, 40), font, font_scale, (0, 0, 0), font_thickness)

final_result = cv2.vconcat([caption_space, combined_results])

cv2.imwrite(os.path.join(args.outdir, filename[:filename.find('.')] + '_img_depth.png'), final_result)