| import gc |
| import logging |
| import os |
| import tempfile |
| import uuid |
|
|
| import torch |
|
|
|
|
| logger = logging.getLogger(__name__) |
|
|
|
|
| class Utils: |
| def __init__(self, host: str = "0.0.0.0", port: int = 8500): |
| self.service_url = f"http://{host}:{port}" |
| self.image_dir = os.path.join(tempfile.gettempdir(), "images") |
| if not os.path.exists(self.image_dir): |
| os.makedirs(self.image_dir) |
|
|
| self.video_dir = os.path.join(tempfile.gettempdir(), "videos") |
| if not os.path.exists(self.video_dir): |
| os.makedirs(self.video_dir) |
|
|
| def save_image(self, image): |
| if hasattr(image, "to"): |
| try: |
| image = image.to("cpu") |
| except Exception: |
| pass |
|
|
| if isinstance(image, torch.Tensor): |
| from torchvision import transforms |
|
|
| to_pil = transforms.ToPILImage() |
| image = to_pil(image.squeeze(0).clamp(0, 1)) |
|
|
| filename = "img" + str(uuid.uuid4()).split("-")[0] + ".png" |
| image_path = os.path.join(self.image_dir, filename) |
| logger.info(f"Saving image to {image_path}") |
|
|
| image.save(image_path, format="PNG", optimize=True) |
|
|
| del image |
| gc.collect() |
| if torch.cuda.is_available(): |
| torch.cuda.empty_cache() |
|
|
| return os.path.join(self.service_url, "images", filename) |
|
|
