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car-detection-bayes
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scripts: use data config defined class names 

Shorten name of --data-config-path argument to --data-config
This commit is contained in:
Guillermo García 2018-12-05 14:52:40 +01:00
parent 89daa407e5
commit 9c0c1f23ab
3 changed files with 13 additions and 15 deletions
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10
detect.py
View File

@ -10,6 +10,7 @@ from utils import torch_utils
def detect( def detect(
net_config_path, net_config_path,
data_config_path,
images_path, images_path,
weights_file_path='weights/yolov3.pt', weights_file_path='weights/yolov3.pt',
output='output', output='output',
@ -19,7 +20,6 @@ def detect(
nms_thres=0.45, nms_thres=0.45,
save_txt=False, save_txt=False,
save_images=False, save_images=False,
class_path='data/coco.names',
): ):
device = torch_utils.select_device() device = torch_utils.select_device()
@ -28,6 +28,8 @@ def detect(
os.system('rm -rf ' + output) os.system('rm -rf ' + output)
os.makedirs(output, exist_ok=True) os.makedirs(output, exist_ok=True)
data_config = parse_data_config(data_config_path)
# Load model # Load model
model = Darknet(net_config_path, img_size) model = Darknet(net_config_path, img_size)
@ -55,7 +57,7 @@ def detect(
model.to(device).eval() model.to(device).eval()
# Set Dataloader # Set Dataloader
classes = load_classes(class_path) # Extracts class labels from file classes = load_classes(data_config['names']) # Extracts class labels from file
dataloader = load_images(images_path, batch_size=batch_size, img_size=img_size) dataloader = load_images(images_path, batch_size=batch_size, img_size=img_size)
imgs = [] # Stores image paths imgs = [] # Stores image paths
@ -151,7 +153,7 @@ if __name__ == '__main__':
parser.add_argument('--txt-out', type=bool, default=False) parser.add_argument('--txt-out', type=bool, default=False)
parser.add_argument('--cfg', type=str, default='cfg/yolov3.cfg', help='cfg file path') parser.add_argument('--cfg', type=str, default='cfg/yolov3.cfg', help='cfg file path')
parser.add_argument('--class-path', type=str, default='data/coco.names', help='path to class label file') parser.add_argument('--data-config', type=str, default='cfg/coco.data', help='path to data config file')
parser.add_argument('--conf-thres', type=float, default=0.50, help='object confidence threshold') parser.add_argument('--conf-thres', type=float, default=0.50, help='object confidence threshold')
parser.add_argument('--nms-thres', type=float, default=0.45, help='iou threshold for non-maximum suppression') parser.add_argument('--nms-thres', type=float, default=0.45, help='iou threshold for non-maximum suppression')
parser.add_argument('--batch-size', type=int, default=1, help='size of the batches') parser.add_argument('--batch-size', type=int, default=1, help='size of the batches')
@ -165,6 +167,7 @@ if __name__ == '__main__':
detect( detect(
opt.cfg, opt.cfg,
opt.data_config,
opt.image_folder, opt.image_folder,
output=opt.output_folder, output=opt.output_folder,
batch_size=opt.batch_size, batch_size=opt.batch_size,
@ -173,5 +176,4 @@ if __name__ == '__main__':
nms_thres=opt.nms_thres, nms_thres=opt.nms_thres,
save_txt=opt.txt_out, save_txt=opt.txt_out,
save_images=opt.plot_flag, save_images=opt.plot_flag,
class_path=opt.class_path,
) )

10
test.py
View File

@ -11,7 +11,6 @@ def test(
net_config_path, net_config_path,
data_config_path, data_config_path,
weights_file_path, weights_file_path,
class_path=None,
batch_size=16, batch_size=16,
img_size=416, img_size=416,
iou_thres=0.5, iou_thres=0.5,
@ -118,8 +117,7 @@ def test(
# Print mAP per class # Print mAP per class
print('%11s' * 5 % ('Image', 'Total', 'P', 'R', 'mAP') + '\n\nmAP Per Class:') print('%11s' * 5 % ('Image', 'Total', 'P', 'R', 'mAP') + '\n\nmAP Per Class:')
if class_path: classes = load_classes(data_config['names']) # Extracts class labels from file
classes = load_classes(class_path) # Extracts class labels from file
for i, c in enumerate(classes): for i, c in enumerate(classes):
print('%15s: %-.4f' % (c, AP_accum[i] / AP_accum_count[i])) print('%15s: %-.4f' % (c, AP_accum[i] / AP_accum_count[i]))
@ -132,9 +130,8 @@ if __name__ == '__main__':
parser = argparse.ArgumentParser(prog='test.py') parser = argparse.ArgumentParser(prog='test.py')
parser.add_argument('--batch-size', type=int, default=32, help='size of each image batch') parser.add_argument('--batch-size', type=int, default=32, help='size of each image batch')
parser.add_argument('--cfg', type=str, default='cfg/yolov3.cfg', help='path to model config file') parser.add_argument('--cfg', type=str, default='cfg/yolov3.cfg', help='path to model config file')
parser.add_argument('--data-config-path', type=str, default='cfg/coco.data', help='path to data config file') parser.add_argument('--data-config', type=str, default='cfg/coco.data', help='path to data config file')
parser.add_argument('--weights', type=str, default='weights/yolov3.pt', help='path to weights file') parser.add_argument('--weights', type=str, default='weights/yolov3.pt', help='path to weights file')
parser.add_argument('--class-path', type=str, default='data/coco.names', help='path to class label file')
parser.add_argument('--iou-thres', type=float, default=0.5, help='iou threshold required to qualify as detected') parser.add_argument('--iou-thres', type=float, default=0.5, help='iou threshold required to qualify as detected')
parser.add_argument('--conf-thres', type=float, default=0.3, help='object confidence threshold') parser.add_argument('--conf-thres', type=float, default=0.3, help='object confidence threshold')
parser.add_argument('--nms-thres', type=float, default=0.45, help='iou threshold for non-maximum suppression') parser.add_argument('--nms-thres', type=float, default=0.45, help='iou threshold for non-maximum suppression')
@ -147,9 +144,8 @@ if __name__ == '__main__':
mAP = test( mAP = test(
opt.cfg, opt.cfg,
opt.data_config_path, opt.data_config,
opt.weights, opt.weights,
class_path=opt.class_path,
batch_size=opt.batch_size, batch_size=opt.batch_size,
img_size=opt.img_size, img_size=opt.img_size,
iou_thres=opt.iou_thres, iou_thres=opt.iou_thres,

4
train.py
View File

@ -220,7 +220,7 @@ if __name__ == '__main__':
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument('--epochs', type=int, default=100, help='number of epochs') parser.add_argument('--epochs', type=int, default=100, help='number of epochs')
parser.add_argument('--batch-size', type=int, default=16, help='size of each image batch') parser.add_argument('--batch-size', type=int, default=16, help='size of each image batch')
parser.add_argument('--data-config-path', type=str, default='cfg/coco.data', help='data config file path') parser.add_argument('--data-config', type=str, default='cfg/coco.data', help='path to data config file')
parser.add_argument('--cfg', type=str, default='cfg/yolov3.cfg', help='cfg file path') parser.add_argument('--cfg', type=str, default='cfg/yolov3.cfg', help='cfg file path')
parser.add_argument('--multi-scale', default=False, help='random image sizes per batch 320 - 608') parser.add_argument('--multi-scale', default=False, help='random image sizes per batch 320 - 608')
parser.add_argument('--img-size', type=int, default=32 * 13, help='pixels') parser.add_argument('--img-size', type=int, default=32 * 13, help='pixels')
@ -236,7 +236,7 @@ if __name__ == '__main__':
torch.cuda.empty_cache() torch.cuda.empty_cache()
train( train(
opt.cfg, opt.cfg,
opt.data_config_path, opt.data_config,
img_size=opt.img_size, img_size=opt.img_size,
resume=opt.resume, resume=opt.resume,
epochs=opt.epochs, epochs=opt.epochs,