Hello, im doing tutorial by Dusty called “Re-training on the Cat/Dog Dataset”. This Tutorial is using the ResNet-18 model . I want to change to a different model. To change model, it says - " you can change that with the
--arch flag." So my question is how to use --arch to change model , i tried this, but not working - “python3 train.py --model-dir=models/cat_dog --batch-size=4 --workers=1 --epochs=1
here is link tutorial :
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<img src="https://github.com/dusty-nv/jetson-inference/raw/master/docs/images/deep-vision-header.jpg" width="100%">
<p align="right"><sup><a href="pytorch-transfer-learning.md">Back</a> | <a href="pytorch-plants.md">Next</a> | </sup><a href="../README.md#hello-ai-world"><sup>Contents</sup></a>
<sup>Transfer Learning - Classification</sup></s></p>
# Re-training on the Cat/Dog Dataset
The first model that we'll be re-training is a simple model that recognizes two classes: cat or dog.
<img src="https://github.com/dusty-nv/jetson-inference/raw/python/docs/images/pytorch-cat-dog.jpg" width="700">
Provided below is an 800MB dataset that includes 5000 training images, 1000 validation images, and 200 test images, each evenly split between the cat and dog classes. The set of training images is used for transfer learning, while the validation set is used to evaluate classification accuracy during training, and the test images are to be used by us after training completes. The network is never directly trained on the validation and test sets, only the training set.
The images from the dataset are made up of many different breeds of dogs and cats, including large felines like tigers and mountain lions since the amount of cat images available was a bit lower than dogs. Some of the images also picture humans, which the detector is essentially trained to ignore as background and focus on the cat vs. dog content.
To get started, first make sure that you have [PyTorch installed](pytorch-transfer-learning.md#installing-pytorch) on your Jetson, then download the dataset below and kick off the training script. After that, we'll test the re-trained model in TensorRT on some static images and a live camera feed.
## Downloading the Data
During this tutorial, we'll store the datasets on the host device under `jetson-inference/python/training/classification/data`, which is one of the directories that is automatically [mounted into the container](aux-docker.md#mounted-data-volumes). This way the dataset won't be lost when you shutdown the container.
@betman15050, can you try it with
Hello Dusty, sorry for taking your time, yes it works that way. Thank you.
вт, 29 нояб. 2022 г. в 23:23, dusty_nv via NVIDIA Developer Forums <
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