def get_configuration():
# load configs for detector, base network and data set
from FasterRCNN_config import cfg as detector_cfg
from utils.configs.VGG16_config import cfg as network_cfg
from utils.configs.Building100_config import cfg as dataset_cfg
return merge_configs([detector_cfg, network_cfg, dataset_cfg])
def get_configuration_resnet50(EPOCH):
# load configs for detector, base network and data set
from utils.configs.FasterRCNN_config import cfg as detector_cfg
from utils.configs.ResNet50_config import cfg as network_cfg
from user_config import cfg as dataset_cfg
detector_cfg["CNTK"].E2E_MAX_EPOCHS=EPOCH
dataset_cfg["DATA"].NUM_TRAIN_IMAGES=count("../"+dataset_cfg["DATA"].TRAIN_MAP_FILE)
return merge_configs([detector_cfg, network_cfg, dataset_cfg])
def getConfiguration(detector_name):
from FasterRCNN.FasterRCNN_config import cfg as detector_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.Prometheus_config import cfg as dataset_cfg
return merge_configs(
[detector_cfg, network_cfg, dataset_cfg, {
'DETECTOR': detector_name
}])
def get_configuration():
# load configs for detector, base network and data set
from FasterRCNN_config import cfg as detector_cfg
# for VGG16 base model use: from utils.configs.VGG16_config import cfg as network_cfg
# for AlexNet base model use: from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
# for Pascal VOC 2007 data set use: from utils.configs.Pascal_config import cfg as dataset_cfg
from utils.configs.GoogleQuickDraw import cfg as dataset_cfg
return merge_configs([detector_cfg, network_cfg, dataset_cfg])
def get_configuration():
# load configs for detector, base network and data set
from FasterRCNN_config import cfg as detector_cfg
# for VGG16 base model use: from utils.configs.VGG16_config import cfg as network_cfg
# for AlexNet base model use: from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
# for Pascal VOC 2007 data set use: from utils.configs.Pascal_config import cfg as dataset_cfg
# for the Grocery data set use: from utils.configs.Grocery_config import cfg as dataset_cfg
from utils.configs.Grocery_config import cfg as dataset_cfg
return merge_configs([detector_cfg, network_cfg, dataset_cfg])
def get_configuration():
# load configs for detector, base network and data set
from FasterRCNN_config import cfg as detector_cfg
# for VGG16 base model use: from utils.configs.VGG16_config import cfg as network_cfg
# for AlexNet base model use: from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
# for NO3310 data set use: from utils.configs.NO3310_config import cfg as dataset_cfg
from utils.configs.NO3310_config import cfg as dataset_cfg
return merge_configs([detector_cfg, network_cfg, dataset_cfg])
def get_configuration():
# load configs for detector, base network and data set
from uploads.core.FastRCNN_config import cfg as detector_cfg
# for VGG16 base model use: from utils.configs.VGG16_config import cfg as network_cfg
# for AlexNet base model use: from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
# for Pascal VOC 2007 data set use: from utils.configs.Pascal_config import cfg as dataset_cfg
# for the Grocery data set use: from utils.configs.Grocery_config import cfg as dataset_cfg
from utils.configs.Grocery_config import cfg as dataset_cfg
return merge_configs([detector_cfg, network_cfg, dataset_cfg])
def get_configuration(detector_name):
# load configs for detector, base network and data set
from FasterRCNN.FasterRCNN_config import cfg as detector_cfg
# AlexNet base model
from utils.configs.AlexNet_config import cfg as network_cfg
# BU (Beijing University) data set
from utils.configs.BU_config import cfg as dataset_cfg
return merge_configs(
[detector_cfg, network_cfg, dataset_cfg, {
'DETECTOR': detector_name
}])
def get_configuration(detector_name):
# load configs for detector, base network and data set
from FasterRCNN.FasterRCNN_config import cfg as detector_cfg
# for AlexNet base model use: from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
# for the Fire data set use: from utils.configs.Prometheus_config import cfg as dataset_cfg
from utils.configs.Prometheus_config import cfg as dataset_cfg
return merge_configs(
[detector_cfg, network_cfg, dataset_cfg, {
'DETECTOR': detector_name
}])
def getConfiguration(detector_name):
# load configs for detector, base network and data set
if detector_name == "FastRCNN":
from FastRCNN.FastRCNN_config import cfg as detector_cfg
elif detector_name == "FasterRCNN":
from FasterRCNN.FasterRCNN_config import cfg as detector_cfg
else:
print('Unknown detector: {}'.format(detector_name))
from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.Prometheus_config import cfg as dataset_cfg
return merge_configs([detector_cfg, network_cfg, dataset_cfg, {'DETECTOR': detector_name}])
def get_configuration(classes):
# load configs for detector, base network and data set
from FasterRCNN.FasterRCNN_config import cfg as detector_cfg
# for VGG16 base model use: from utils.configs.VGG16_config import cfg as network_cfg
# for AlexNet base model use: from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
dataset_cfg = generate_data_cfg(classes)
return merge_configs([
detector_cfg, network_cfg, dataset_cfg, {
'DETECTOR': 'FasterRCNN'
}
])
def get_configuration():
from FasterRCNN.FasterRCNN_config import cfg as detector_cfg
# for VGG16 base model use: from utils.configs.VGG16_config import cfg as network_cfg
# for AlexNet base model use: from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
# for Pascal VOC 2007 data set use: from utils.configs.Pascal_config import cfg as dataset_cfg
from utils.configs.GoogleQuickDraw_config import cfg as dataset_cfg
return merge_configs(
[detector_cfg, network_cfg, dataset_cfg, {
'DETECTOR': 'FasterRCNN'
}])
def __init__(self, model_type):
self.cfg = merge_configs([
detector_cfg, network_cfg, dataset_cfg, {
'DETECTOR': 'FasterRCNN'
}
])
self.name = "TNC_faster_rcnn_eval_AlexNet_e2e_native.model"
self.model_type = ''
self.model_path = ''
self.model_file = ''
self.en_zh_file = ''
self.en_zh_dict = {}
self.eval_model = None
self.evaluator = None
self.set_model_type(model_type)
return
def get_configuration(detector_name):
# load configs for detector, base network and data set
if detector_name == "FastRCNN":
from FastRCNN.FastRCNN_config import cfg as detector_cfg
elif detector_name == "FasterRCNN":
from FasterRCNN.FasterRCNN_config import cfg as detector_cfg
else:
print('Unknown detector: {}'.format(detector_name))
# for VGG16 base model use: from utils.configs.VGG16_config import cfg as network_cfg
# for AlexNet base model use: from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
# for Pascal VOC 2007 data set use: from utils.configs.Pascal_config import cfg as dataset_cfg
# for the Grocery data set use: from utils.configs.Grocery_config import cfg as dataset_cfg
from utils.configs.Grocery_config import cfg as dataset_cfg
return merge_configs([detector_cfg, network_cfg, dataset_cfg, {'DETECTOR': detector_name}])
def test_fastrcnnpy_grocery_training(device_id):
if cntk_device(device_id).type() != DeviceKind_GPU:
pytest.skip('test only runs on GPU') # it runs very slow in CPU
try_set_default_device(cntk_device(device_id))
from utils.config_helpers import merge_configs
from FastRCNN_config import cfg as detector_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.Grocery_config import cfg as dataset_cfg
cfg = merge_configs([detector_cfg, network_cfg, dataset_cfg])
cfg["CNTK"].FORCE_DETERMINISTIC = True
cfg["CNTK"].DEBUG_OUTPUT = False
cfg["CNTK"].MAKE_MODE = False
cfg["CNTK"].FAST_MODE = False
cfg["CNTK"].MAX_EPOCHS = 4
cfg.IMAGE_WIDTH = 600
cfg.IMAGE_HEIGHT = 600
cfg.NUM_ROI_PROPOSALS = 200
cfg.USE_GPU_NMS = False
cfg.VISUALIZE_RESULTS = False
cfg["DATA"].MAP_FILE_PATH = grocery_path
externalData = 'CNTK_EXTERNAL_TESTDATA_SOURCE_DIRECTORY' in os.environ
if externalData:
extPath = os.environ['CNTK_EXTERNAL_TESTDATA_SOURCE_DIRECTORY']
cfg['BASE_MODEL_PATH'] = os.path.join(extPath, "PreTrainedModels",
"AlexNet", "v1",
"AlexNet_ImageNet_Caffe.model")
else:
cfg['BASE_MODEL_PATH'] = os.path.join(
abs_path,
*"../../../../PretrainedModels/AlexNet_ImageNet_Caffe.model".split(
"/"))
from FastRCNN_train import prepare, train_fast_rcnn
from FastRCNN_eval import compute_test_set_aps
prepare(cfg, False)
np.random.seed(seed=3)
trained_model = train_fast_rcnn(cfg)
eval_results = compute_test_set_aps(trained_model, cfg)
meanAP = np.nanmean(list(eval_results.values()))
print('meanAP={}'.format(meanAP))
assert meanAP > 0.01
def get_configuration():
# load configs for detector, base network and data set
from FasterRCNN.FasterRCNN_config import cfg as detector_cfg
# for VGG16 base model use: from utils.configs.VGG16_config import cfg as network_cfg
# for AlexNet base model use: from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
# for Pascal VOC 2007 data set use: from utils.configs.Pascal_config import cfg as dataset_cfg
# for the Grocery data set use: from utils.configs.Grocery_config import cfg as dataset_cfg
# from utils.configs.Grocery_config import cfg as dataset_cfg
###################################################################
# Custom Dataset NO3310
from utils.configs.NO3310_config import cfg as dataset_cfg
return merge_configs(
[detector_cfg, network_cfg, dataset_cfg, {
'DETECTOR': 'FasterRCNN'
}])
def run_fasterrcnn_grocery_training(e2e):
from FasterRCNN_eval import compute_test_set_aps
from utils.config_helpers import merge_configs
from FasterRCNN_config import cfg as detector_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.Grocery_config import cfg as dataset_cfg
cfg = merge_configs([detector_cfg, network_cfg, dataset_cfg])
cfg["CNTK"].FORCE_DETERMINISTIC = True
cfg["CNTK"].DEBUG_OUTPUT = False
cfg["CNTK"].MAKE_MODE = False
cfg["CNTK"].FAST_MODE = False
cfg.CNTK.E2E_MAX_EPOCHS = 3
cfg.CNTK.RPN_EPOCHS = 2
cfg.CNTK.FRCN_EPOCHS = 2
cfg.IMAGE_WIDTH = 400
cfg.IMAGE_HEIGHT = 400
cfg["CNTK"].TRAIN_E2E = e2e
cfg.USE_GPU_NMS = False
cfg.VISUALIZE_RESULTS = False
cfg["DATA"].MAP_FILE_PATH = grocery_path
externalData = 'CNTK_EXTERNAL_TESTDATA_SOURCE_DIRECTORY' in os.environ
if externalData:
extPath = os.environ['CNTK_EXTERNAL_TESTDATA_SOURCE_DIRECTORY']
model_file = os.path.join(extPath, "PreTrainedModels", "AlexNet", "v1",
"AlexNet_ImageNet_Caffe.model")
else:
model_file = os.path.join(
abs_path,
*"../../../../PretrainedModels/AlexNet_ImageNet_Caffe.model".split(
"/"))
from FasterRCNN_train import prepare, train_faster_rcnn
np.random.seed(seed=3)
prepare(cfg, False)
cfg['BASE_MODEL_PATH'] = model_file
trained_model = train_faster_rcnn(cfg)
eval_results = compute_test_set_aps(trained_model, cfg)
meanAP = np.nanmean(list(eval_results.values()))
print('meanAP={}'.format(meanAP))
assert meanAP > 0.01
return trained_model, meanAP, cfg
def evaluate(model_path):
# ProposalLayer currently only runs on the CPU
eval_device = C.cpu()
model = C.Function.load(model_path, device=eval_device)
from FasterRCNN.FasterRCNN_config import cfg as detector_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.Grocery_config import cfg as dataset_cfg
from utils.config_helpers import merge_configs
from FasterRCNN.FasterRCNN_train import prepare
from FasterRCNN.FasterRCNN_eval import compute_test_set_aps
cfg = merge_configs([detector_cfg, network_cfg, dataset_cfg])
cfg["CNTK"].FORCE_DETERMINISTIC = True
prepare(cfg, False)
eval_results = compute_test_set_aps(model, cfg)
meanAP = np.nanmean(list(eval_results.values()))
return meanAP
def evaluate(model_path):
# ProposalLayer currently only runs on the CPU
eval_device = C.cpu()
model = C.Function.load(model_path, device=eval_device)
from FasterRCNN.FasterRCNN_config import cfg as detector_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.Grocery_config import cfg as dataset_cfg
from utils.config_helpers import merge_configs
from FasterRCNN.FasterRCNN_train import prepare
from FasterRCNN.FasterRCNN_eval import compute_test_set_aps
cfg = merge_configs([detector_cfg, network_cfg, dataset_cfg])
cfg["CNTK"].FORCE_DETERMINISTIC = True
prepare(cfg, False)
eval_results = compute_test_set_aps(model, cfg)
meanAP = np.nanmean(list(eval_results.values()))
return meanAP
def get_configuration(detector_name):
# load configs for detector, base network and data set
if detector_name == "FastRCNN":
from FastRCNN.FastRCNN_config import cfg as detector_cfg
elif detector_name == "FasterRCNN":
from FasterRCNN.FasterRCNN_config import cfg as detector_cfg
else:
print('Unknown detector: {}'.format(detector_name))
# for VGG16 base model use: from utils.configs.VGG16_config import cfg as network_cfg
# for AlexNet base model use: from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
# for Pascal VOC 2007 data set use: from utils.configs.Pascal_config import cfg as dataset_cfg
# for the Grocery data set use: from utils.configs.Grocery_config import cfg as dataset_cfg
from utils.configs.Grocery_config import cfg as dataset_cfg
return merge_configs(
[detector_cfg, network_cfg, dataset_cfg, {
'DETECTOR': detector_name
}])
def run_fasterrcnn_grocery_training(e2e):
from FasterRCNN_eval import compute_test_set_aps
from utils.config_helpers import merge_configs
from FasterRCNN_config import cfg as detector_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.Grocery_config import cfg as dataset_cfg
cfg = merge_configs([detector_cfg, network_cfg, dataset_cfg])
cfg["CNTK"].FORCE_DETERMINISTIC = True
cfg["CNTK"].DEBUG_OUTPUT = False
cfg["CNTK"].MAKE_MODE = False
cfg["CNTK"].FAST_MODE = False
cfg.CNTK.E2E_MAX_EPOCHS = 3
cfg.CNTK.RPN_EPOCHS = 2
cfg.CNTK.FRCN_EPOCHS = 2
cfg.IMAGE_WIDTH = 400
cfg.IMAGE_HEIGHT = 400
cfg["CNTK"].TRAIN_E2E = e2e
cfg.USE_GPU_NMS = False
cfg.VISUALIZE_RESULTS = False
cfg["DATA"].MAP_FILE_PATH = grocery_path
externalData = 'CNTK_EXTERNAL_TESTDATA_SOURCE_DIRECTORY' in os.environ
if externalData:
extPath = os.environ['CNTK_EXTERNAL_TESTDATA_SOURCE_DIRECTORY']
model_file = os.path.join(extPath, "PreTrainedModels", "AlexNet", "v1", "AlexNet_ImageNet_Caffe.model")
else:
model_file = os.path.join(abs_path, *"../../../../PretrainedModels/AlexNet_ImageNet_Caffe.model".split("/"))
from FasterRCNN_train import prepare, train_faster_rcnn
np.random.seed(seed=3)
prepare(cfg, False)
cfg['BASE_MODEL_PATH'] = model_file
trained_model = train_faster_rcnn(cfg)
eval_results = compute_test_set_aps(trained_model, cfg)
meanAP = np.nanmean(list(eval_results.values()))
print('meanAP={}'.format(meanAP))
assert meanAP > 0.01
return trained_model, meanAP, cfg
def test_fastrcnnpy_grocery_training(device_id):
if cntk_device(device_id).type() != DeviceKind_GPU:
pytest.skip('test only runs on GPU') # it runs very slow in CPU
try_set_default_device(cntk_device(device_id))
from utils.config_helpers import merge_configs
from FastRCNN_config import cfg as detector_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.Grocery_config import cfg as dataset_cfg
cfg = merge_configs([detector_cfg, network_cfg, dataset_cfg])
cfg["CNTK"].FORCE_DETERMINISTIC = True
cfg["CNTK"].DEBUG_OUTPUT = False
cfg["CNTK"].MAKE_MODE = False
cfg["CNTK"].FAST_MODE = False
cfg["CNTK"].MAX_EPOCHS = 4
cfg.IMAGE_WIDTH = 600
cfg.IMAGE_HEIGHT = 600
cfg.NUM_ROI_PROPOSALS = 200
cfg.USE_GPU_NMS = False
cfg.VISUALIZE_RESULTS = False
cfg["DATA"].MAP_FILE_PATH = grocery_path
externalData = 'CNTK_EXTERNAL_TESTDATA_SOURCE_DIRECTORY' in os.environ
if externalData:
extPath = os.environ['CNTK_EXTERNAL_TESTDATA_SOURCE_DIRECTORY']
cfg['BASE_MODEL_PATH'] = os.path.join(extPath, "PreTrainedModels", "AlexNet", "v1", "AlexNet_ImageNet_Caffe.model")
else:
cfg['BASE_MODEL_PATH'] = os.path.join(abs_path, *"../../../../PretrainedModels/AlexNet_ImageNet_Caffe.model".split("/"))
from FastRCNN_train import prepare, train_fast_rcnn
from FastRCNN_eval import compute_test_set_aps
prepare(cfg, False)
np.random.seed(seed=3)
trained_model = train_fast_rcnn(cfg)
eval_results = compute_test_set_aps(trained_model, cfg)
meanAP = np.nanmean(list(eval_results.values()))
print('meanAP={}'.format(meanAP))
assert meanAP > 0.01
def get_configuration():
from FasterRCNN_config import cfg as detector_cfg
from utils.configs.VGG16_config import cfg as network_cfg
from utils.configs.Custom_config import cfg as dataset_cfg
return merge_configs([detector_cfg, network_cfg, dataset_cfg])
def get_configuration():
from utils.config_helpers import merge_configs
from FasterRCNN_config import cfg as detector_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
from utils.configs.custom_image_config import cfg as dataset_cfg
return merge_configs([detector_cfg, network_cfg, dataset_cfg])
def set_vars():
global args
parser = argparse.ArgumentParser()
parser.add_argument('-c',
'--config',
help='Config file in YAML format',
required=True,
default=None)
args = vars(parser.parse_args())
# trains and evaluates a Fast R-CNN model.
if __name__ == '__main__':
set_vars()
yaml_config = cfg_from_file(args['config'])
cfg = merge_configs([detector_cfg, yaml_config])
prepare(cfg, False)
setup(cfg)
cntk.device.try_set_default_device(cntk.device.gpu(cfg.GPU_ID))
# train and test
trained_model = train_faster_rcnn(cfg)
eval_results = compute_test_set_aps(trained_model, cfg)
# write AP results to output
for class_name in eval_results:
print('AP for {:>15} = {:.4f}'.format(class_name,
eval_results[class_name]))
print('Mean AP = {:.4f}'.format(np.nanmean(list(eval_results.values()))))
# copy trained model to specified location in config YAML file
def get_configuration_alexnet():
# load configs for detector, base network and data set
from utils.configs.FasterRCNN_config import cfg as detector_cfg
from utils.configs.AlexNet_config import cfg as network_cfg
from user_config import cfg as dataset_cfg
return merge_configs([detector_cfg, network_cfg, dataset_cfg])
