def test_imagenet_model(model_name, val_data, gpus, batch_size):
"""test model on imagenet """
logging.info('test %s', model_name)
meta_info = get_model_meta_info(model_name)
[model_name, mean] = convert_caffe_model(model_name, meta_info)
sym, arg_params, aux_params = mx.model.load_checkpoint(model_name, 0)
acc = [mx.metric.create('acc'), mx.metric.create('top_k_accuracy', top_k=5)]
if isinstance(mean, str):
mean_args = {'mean_img':mean}
else:
mean_args = {'rgb_mean':','.join([str(i) for i in mean])}
print(val_data)
(speed,) = score(model=(sym, arg_params, aux_params),
data_val=val_data,
label_name='prob_label',
metrics=acc,
gpus=gpus,
batch_size=batch_size,
max_num_examples=500,
**mean_args)
logging.info('speed : %f image/sec', speed)
for a in acc:
logging.info(a.get())
assert acc[0].get()[1] > meta_info['top-1-acc'] - 0.3
assert acc[1].get()[1] > meta_info['top-5-acc'] - 0.3
def test_model_weights_and_outputs(model_name, image_url, gpu):
"""
Run the layer comparison on one of the known caffe models.
:param model_name: available models are listed in convert_caffe_modelzoo.py
:param image_url: image file or url to run inference on
:param gpu: gpu to use, -1 for cpu
"""
logging.info('test weights and outputs of model: %s', model_name)
meta_info = get_model_meta_info(model_name)
(prototxt, caffemodel, mean) = download_caffe_model(model_name, meta_info, dst_dir='./model')
convert_and_compare_caffe_to_mxnet(image_url, gpu, prototxt, caffemodel, mean,
mean_diff_allowed=1e-03, max_diff_allowed=1e-01)
def test_model_weights_and_outputs(model_name, image_url, gpu):
"""
Run the layer comparison on one of the known caffe models.
:param model_name: available models are listed in convert_caffe_modelzoo.py
:param image_url: image file or url to run inference on
:param gpu: gpu to use, -1 for cpu
"""
logging.info('test weights and outputs of model: %s', model_name)
meta_info = get_model_meta_info(model_name)
(prototxt, caffemodel, mean) = download_caffe_model(model_name, meta_info, dst_dir='./model')
convert_and_compare_caffe_to_mxnet(image_url, gpu, prototxt, caffemodel, mean,
mean_diff_allowed=1e-03, max_diff_allowed=1e-01)
