Day #227 - Learning Re-Id

1. Installed the Pytorch framework for deep-learning person re-identification - Link
2. Followed the steps commenting out the GPU code and ran it on CPU
3. Code to Check Available Models

	from torchreid import models
	print(models.show_avai_models())

view raw reid_example2.py hosted with ❤ by GitHub

4. Running it on Other Datasets

	import torchreid
	datamanager = torchreid.data.ImageDataManager(
	root='reid-data',
	sources='market1501',
	height=256,
	width=128,
	batch_size=32,
	market1501_500k=False)
	model = torchreid.models.build_model(
	name = 'resnet50',
	num_classes = datamanager.num_train_pids,
	loss='softmax',
	pretrained=True)
	optimizer = torchreid.optim.build_optimizer(
	model,
	optim='adam',
	lr=0.0003)
	scheduler = torchreid.optim.build_lr_scheduler(
	optimizer,
	lr_scheduler='single_step',
	stepsize=20)
	engine = torchreid.engine.ImageSoftmaxEngine(datamanager,
	model,
	optimizer=optimizer,
	scheduler=scheduler,
	label_smooth=True)
	engine.run(save_dir='log/resnet50',
	max_epoch=60,
	eval_freq=10,
	print_freq=10,
	test_only=False)

view raw Reid_example1.py hosted with ❤ by GitHub

5. Next Step - On Custom Dataset Setting up, Testing Models

Happy Mastering DL!!!