Depth Anything is a highly practical solution for robust monocular depth estimation.
We strongly recommend using a virtual environment. If you're not sure where to start, we offer a tutorial here.
pip install ikomia
from ikomia.dataprocess.workflow import Workflow
from ikomia.utils.displayIO import display
# Init your workflow
wf = Workflow()
# Add algorithm
algo = wf.add_task(name="infer_depth_anything", auto_connect=True)
# Run directly on your image
wf.run_on(url="https://github.com/Ikomia-dev/notebooks/blob/main/examples/img/img_dog.png?raw=true")
# Display the results
display(algo.get_input(0).get_image())
display(algo.get_output(0).get_image())
Ikomia Studio offers a friendly UI with the same features as the API.
- If you haven't started using Ikomia Studio yet, download and install it from this page.
- For additional guidance on getting started with Ikomia Studio, check out this blog post.
- model_name (str) - default 'LiheYoung/depth-anything-base-hf': Name of the ViT pre-trained model.
- 'LiheYoung/depth-anything-small-hf' ; Param: 24.8M
- 'LiheYoung/depth-anything-base-hf' ; Param: 97.5M
- 'LiheYoung/depth-anything-large-hf' ; Param: 335.3M
- cuda (bool): If True, CUDA-based inference (GPU). If False, run on CPU.
from ikomia.dataprocess.workflow import Workflow
from ikomia.utils.displayIO import display
# Init your workflow
wf = Workflow()
# Add algorithm
algo = wf.add_task(name="infer_depth_anything", auto_connect=True)
algo.set_parameters({
'model_name':'LiheYoung/depth-anything-base-hf',
'cuda':'True'})
# Run directly on your image
wf.run_on(url="https://github.com/Ikomia-dev/notebooks/blob/main/examples/img/img_dog.png?raw=true")
# Display the results
display(algo.get_input(0).get_image())
display(algo.get_output(0).get_image())
Every algorithm produces specific outputs, yet they can be explored them the same way using the Ikomia API. For a more in-depth understanding of managing algorithm outputs, please refer to the documentation.
from ikomia.dataprocess.workflow import Workflow
# Init your workflow
wf = Workflow()
# Add algorithm
algo = wf.add_task(name="infer_depth_anything", auto_connect=True)
# Run on your image
wf.run_on(url="https://github.com/Ikomia-dev/notebooks/blob/main/examples/img/img_dog.png?raw=true")
# Iterate over outputs
for output in algo.get_outputs():
# Print information
print(output)
# Export it to JSON
output.to_json()