|
import torch
|
|
from torchvision import transforms
|
|
from huggingface_hub import hf_hub_download
|
|
import json
|
|
import io
|
|
import base64
|
|
from PIL import Image
|
|
from omegaconf import OmegaConf
|
|
|
|
from model import Generator
|
|
|
|
|
|
class EndpointHandler:
|
|
|
|
def __init__(self, path=''):
|
|
self.transform = transforms.Compose(
|
|
[
|
|
transforms.ToImage(),
|
|
transforms.ToDtype(torch.float32, scale=True),
|
|
transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]),
|
|
]
|
|
)
|
|
|
|
repo_id = "Kiwinicki/sat2map-generator"
|
|
generator_path = hf_hub_download(repo_id=repo_id, filename="generator.pth")
|
|
config_path = hf_hub_download(repo_id=repo_id, filename="config.json")
|
|
model_path = hf_hub_download(repo_id=repo_id, filename="model.py")
|
|
|
|
with open(config_path, "r") as f:
|
|
config_dict = json.load(f)
|
|
cfg = OmegaConf.create(config_dict)
|
|
|
|
self.generator = Generator(cfg)
|
|
self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
|
|
self.generator.load_state_dict(torch.load(generator_path, map_location=self.device))
|
|
self.generator.eval()
|
|
|
|
|
|
def __call__(self, data: dict[str, any]) -> dict[str, str]:
|
|
base64_image = data.get('inputs')
|
|
input_tensor = self._decode_base64_image(base64_image)
|
|
|
|
output_tensor = self.generator(input_tensor.to(self.device))
|
|
output_tensor = output_tensor.squeeze(0)
|
|
output_image = transforms.ToPILImage()(output_tensor)
|
|
output_image = output_image.convert('RGB')
|
|
output_buffer = io.BytesIO()
|
|
output_image.save(output_buffer, format="png")
|
|
base64_output = base64.b64encode(output_buffer.getvalue()).decode('utf-8')
|
|
return {"output": base64_output}
|
|
|
|
|
|
def _decode_base64_image(self, base64_image: str) -> torch.Tensor:
|
|
image_decoded = base64.b64decode(base64_image)
|
|
image = Image.open(io.BytesIO(image_decoded)).convert('RGB')
|
|
image_tensor: torch.Tensor = self.transform(image)
|
|
image_tensor = image_tensor.unsqueeze(0)
|
|
return image_tensor
|
|
|
