Spaces:
Sleeping
Sleeping
File size: 1,809 Bytes
640ea1d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
# https://github.com/fcakyon/yolov5-pip/blob/main/yolov5/helpers.py
import sys
from pathlib import Path
FILE = Path(__file__).resolve()
ROOT = FILE.parents[0] # YOLOv5 root directory
if str(ROOT) not in sys.path:
sys.path.append(str(ROOT)) # add ROOT to PATH
from pathlib import Path
from PIL import Image
from yolov7.models.common import autoShape
from yolov7.models.experimental import attempt_load
from yolov7.utils.google_utils import attempt_download_from_hub, attempt_download
from yolov7.utils.torch_utils import TracedModel
def load_model(model_path, autoshape=True, device='cpu', trace=False, size=640, half=False, hf_model=False):
"""
Creates a specified YOLOv7 model
Arguments:
model_path (str): path of the model
device (str): select device that model will be loaded (cpu, cuda)
trace (bool): if True, model will be traced
size (int): size of the input image
half (bool): if True, model will be in half precision
hf_model (bool): if True, model will be loaded from huggingface hub
Returns:
pytorch model
(Adapted from yolov7.hubconf.create)
"""
if hf_model:
model_file = attempt_download_from_hub(model_path)
else:
model_file = attempt_download(model_path)
model = attempt_load(model_file, map_location=device)
if trace:
model = TracedModel(model, device, size)
if autoshape:
model = autoShape(model)
if half:
model.half()
return model
if __name__ == "__main__":
model_path = "yolov7.pt"
device = "cuda:0"
model = load_model(model_path, device, trace=False, size=640, hf_model=False)
imgs = [Image.open(x) for x in Path("inference/images").glob("*.jpg")]
results = model(imgs, size=640, augment=False)
|