alphapose-feedback/run_test_inferences.py

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from pathlib import Path
import shutil
from loop_alphapose_training import run_cmd, Iteration
import logging
import coloredlogs
logger = logging.getLogger(__name__)
coloredlogs.install(level=logging.INFO)
def collate(iterations):
path = Path(f'out/test_imgs_{iterations[1].nr}/vis')
images = [x for x in path.iterdir() if x.is_file()]
for img in images:
logger.info(f"collate {img.name}")
target_dir = Path(f'out/test_imgs_loops/{img.stem}/')
target_dir.mkdir(parents=True, exist_ok=True)
for iteration in iterations:
try:
src = Path(f'out/test_imgs_{iteration.nr}/vis/') / img.name
target = target_dir / (iteration.nr + img.suffix)
logger.info(f"\tcopy {src} to {target}")
shutil.copy(src, target)
except Exception as e:
logger.exception(e)
# collate([Iteration(i) for i in range(2,7)])
# exit()
if __name__ == '__main__':
i = 0
iterations = []
while True:
i+=1
iteration = Iteration(i)
path = iteration.model_path()
if not path.exists():
logger.warning(f"Model for iteration {iteration.nr} doesn't exist")
break
iterations.append(iteration)
cmd = [
'python', 'scripts/demo_inference.py',
'--cfg', str(iteration.training_config_path()),
'--checkpoint', str(iteration.model_path()),
'--gpus', '0',
'--format', 'coco',
'--indir', 'data/test_imgs',
'--outdir', f'/out/test_imgs_{iteration.nr}',
'--save_img'
]
logger.info(f"Running {cmd}")
run_cmd(cmd, in_docker=True)
# break
collate(iterations)