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Sleeping
File size: 1,855 Bytes
717b5e6 | 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 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 | from fastapi import FastAPI, File, UploadFile
from fastapi.middleware.cors import CORSMiddleware
from ultralytics import YOLO
from PIL import Image
import io
import os
app = FastAPI()
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_methods=["*"],
allow_headers=["*"],
)
# Download and cache model on startup
from huggingface_hub import hf_hub_download
model_path = hf_hub_download(
repo_id="Decizez/yolov-corrosion-detection",
filename="Lite_YOLO8_v1.pt"
)
model = YOLO(model_path)
print("✅ Model loaded successfully")
@app.get("/health")
async def health():
return {"status": "ok"}
@app.post("/detect")
async def detect(file: UploadFile = File(...)):
contents = await file.read()
image = Image.open(io.BytesIO(contents)).convert("RGB")
w, h = image.width, image.height
results = model(image)
detections = []
for result in results:
boxes = result.boxes
if boxes is not None:
for box in boxes:
conf = float(box.conf[0])
if conf > 0.3:
x1, y1, x2, y2 = box.xyxy[0].tolist()
detections.append({
"label": "Corrosion Detected",
"confidence": round(conf * 100, 1),
"area_percent": round(
((x2 - x1) * (y2 - y1)) / (w * h) * 100, 1
),
"box": {
"x": round(x1 / w * 100, 1),
"y": round(y1 / h * 100, 1),
"width": round((x2 - x1) / w * 100, 1),
"height": round((y2 - y1) / h * 100, 1)
}
})
return {
"detections": detections,
"frame_size": {"w": w, "h": h}
}
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