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74846bb | 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 | import torch
from PIL import Image
import io
import torchvision.transforms as T
from ultralytics.nn.tasks import DetectionModel
# YOLOv11 yapılandırması ve ağırlıkları yükle
model = DetectionModel(cfg="yolov11.yaml")
model.load_state_dict(torch.load("yolo_safe.pth", map_location="cpu"))
model.eval()
def preprocess(image_bytes):
image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
transform = T.Compose([
T.Resize((640, 640)),
T.ToTensor()
])
return transform(image).unsqueeze(0)
def postprocess(preds):
result = []
for pred in preds:
for box in pred:
result.append({
"box": {
"xmin": int(box[0]),
"ymin": int(box[1]),
"xmax": int(box[2]),
"ymax": int(box[3])
},
"score": float(box[4]),
"label": str(int(box[5]))
})
return result
def inference(inputs):
image_bytes = inputs["inputs"]
image_tensor = preprocess(image_bytes)
with torch.no_grad():
preds = model(image_tensor)[0]
return postprocess([preds]) |