by Ciro Santilli (@cirosantilli, 32)
pytorch.org/vision/0.13/models.html has a minimal runnable example adapted to python/pytorch/resnet_demo.py.
That example uses a ResNet pre-trained on the COCO dataset to do some inference, tested on Ubuntu 22.10: 
cd python/pytorch
wget -O resnet_demo_in.jpg https://upload.wikimedia.org/wikipedia/commons/thumb/6/60/Rooster_portrait2.jpg/400px-Rooster_portrait2.jpg
./resnet_demo.py resnet_demo_in.jpg resnet_demo_out.jpg
This first downloads the model, which is currently 167 MB.
We know it is COCO because of the docs: pytorch.org/vision/0.13/models/generated/torchvision.models.detection.fasterrcnn_resnet50_fpn_v2.html which explains that 
FasterRCNN_ResNet50_FPN_V2_Weights.DEFAULT
is an alias for: 
FasterRCNN_ResNet50_FPN_V2_Weights.COCO_V1
The runtime is relatively slow on P51, about 4.7s.
After it finishes, the program prints the recognized classes: 
['bird', 'banana']
so we get the expected bird, but also the more intriguing banana.
By looking at the output image with bounding boxes, we understand where the banana came from!
Figure 1. python/pytorch/resnet_demo_in.jpg. Source.
Figure 2. python/pytorch/resnet_demo_out.jpg. The beak was of course a banana, not a beak!

Ancestors

  1. torchvision
  2. PyTorch
  3. Deep learning framework
  4. Deep learning
  5. Artificial neural network
  6. Neural network
  7. Machine learning
  8. Computer
  9. Information technology
  10. Area of technology
  11. Technology
  12. Index

Incoming links

Discussion (0)

Sign up or sign in create discussions.

There are no discussions about this article yet.

View article source