| """Evaluation entrypoint (single process). |
| |
| python framework/test.py --dataset cvc_clinicdb --arch unet --exp_name myrun --seed 0 |
| """ |
| from __future__ import annotations |
|
|
| import os |
| import sys |
|
|
| sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) |
|
|
| import torch |
| import cv2 |
|
|
| |
| |
| cv2.setNumThreads(1) |
|
|
| from framework.config import Config |
| from framework.models.registry import build_model, required_img_size |
| from framework.engine.evaluator import evaluate |
| from framework.data.loaders import build_dataset |
|
|
|
|
| def main(): |
| cfg = Config.from_args() |
| req = required_img_size(cfg.arch) |
| if req and cfg.img_size != req: |
| cfg.img_size = req |
|
|
| if torch.cuda.is_available(): |
| torch.cuda.set_device(0) |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
|
|
| probe = build_dataset(cfg, "test") |
| model = build_model(cfg.arch, in_channels=probe.in_channels, num_classes=probe.num_classes, |
| img_size=cfg.img_size, encoder=cfg.encoder, |
| encoder_weights="none", |
| pretrained_ckpt="") |
| evaluate(cfg, model, device, ckpt_path=cfg.resume) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
