Evaluated classifications onnx models almost with zero accuracy
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Description
I evaluated all of the classifications models according to their preprocessing description with imagenet:
Models:
- squeezenet1.0-12.onnx
- bvlcalexnet-12.onnx
- caffenet-12.onnx
- rcnn-ilsvrc13-9.onnx
- inception-v1-12.onnx
- inception-v2-9.onnx
- zfnet512-12.onnx
Why should this models being in the model zoo if their behavior and accuracy is terrible?
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Research direction
Reproduce the reported evaluations for squeezenet1.0-12.onnx, bvlcalexnet-12.onnx, caffenet-12.onnx, rcnn-ilsvrc13-9.onnx, inception-v1-12.onnx, inception-v2-9.onnx, and zfnet512-12.onnx using ImageNet and each model's preprocessing description. Record the observed accuracy and compare it with the models' expected behavior to determine whether the model files or preprocessing guidance are incorrect.
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Assessment
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100