181 lines
7.2 KiB
Python
181 lines
7.2 KiB
Python
from io import BytesIO
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from fastapi import Depends, FastAPI, File, Form, HTTPException, Request, UploadFile
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from fastapi.responses import HTMLResponse, StreamingResponse
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from app.config import settings
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app = FastAPI(title="face-lock", version="0.3.0")
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def require_auth(request: Request) -> None:
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if not settings.auth_enabled:
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return
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header_name = settings.auth_header_name.lower()
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provided = request.headers.get(header_name)
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if not provided and request.headers.get("authorization", "").lower().startswith("bearer "):
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provided = request.headers.get("authorization", "")[7:].strip()
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if provided != settings.auth_token:
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raise HTTPException(status_code=401, detail="unauthorized")
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@app.get("/health")
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def health():
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return {
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"ok": True,
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"env": settings.env,
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"auth_enabled": settings.auth_enabled,
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"auth_header": settings.auth_header_name if settings.auth_enabled else None,
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}
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@app.get("/", response_class=HTMLResponse)
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def index():
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return HTMLResponse(
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"""
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<!doctype html>
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<html lang="en">
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<head>
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<meta charset="utf-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1" />
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<script src="https://cdn.tailwindcss.com"></script>
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<title>face-lock</title>
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</head>
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<body class="bg-slate-950 text-slate-100 min-h-screen">
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<main class="mx-auto max-w-6xl p-6">
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<div class="mb-6 flex items-center justify-between gap-4">
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<div>
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<h1 class="text-3xl font-bold">face-lock</h1>
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<p class="text-slate-400">Square the subject, crop it, and keep the raw blobs out of sight.</p>
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</div>
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<a class="rounded-lg border border-slate-700 px-3 py-2 text-sm text-cyan-300 hover:bg-slate-900" href="/docs" target="_blank">Docs</a>
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</div>
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<div class="grid gap-6 md:grid-cols-2">
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<section class="rounded-2xl border border-slate-800 bg-slate-900 p-4">
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<label class="block text-sm text-slate-400">Image</label>
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<input id="file" type="file" accept="image/*" class="mt-2 block w-full rounded-lg border border-slate-700 bg-slate-950 p-3" />
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<div class="mt-4 grid gap-4 sm:grid-cols-2">
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<div>
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<label class="block text-sm text-slate-400">Detector</label>
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<select id="detector" class="mt-2 block w-full rounded-lg border border-slate-700 bg-slate-950 p-3">
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<option value="face">Face</option>
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<option value="animal">Animal</option>
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<option value="person">Person</option>
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<option value="subject" selected>Subject</option>
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</select>
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</div>
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<div>
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<label class="block text-sm text-slate-400">Buffer ratio</label>
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<input id="buffer_ratio" type="number" step="0.05" min="0" max="0.6" value="0.20" class="mt-2 block w-full rounded-lg border border-slate-700 bg-slate-950 p-3" />
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</div>
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</div>
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<div class="mt-4">
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<label class="block text-sm text-slate-400">Auth token (only if enabled)</label>
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<input id="auth_token" type="password" placeholder="paste token here" class="mt-2 block w-full rounded-lg border border-slate-700 bg-slate-950 p-3" />
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</div>
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<button id="go" class="mt-4 rounded-lg bg-cyan-500 px-4 py-2 font-semibold text-slate-950">Process</button>
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<pre id="meta" class="mt-4 whitespace-pre-wrap rounded-lg bg-slate-950 p-3 text-xs text-slate-300"></pre>
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</section>
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<section class="rounded-2xl border border-slate-800 bg-slate-900 p-4">
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<div class="mb-3 text-sm font-semibold text-slate-400">Result</div>
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<div class="grid gap-4">
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<div>
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<div class="mb-2 text-xs uppercase tracking-wide text-slate-500">Crop</div>
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<img id="crop" class="hidden w-full rounded-xl border border-slate-800" />
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</div>
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<div>
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<div class="mb-2 text-xs uppercase tracking-wide text-slate-500">Annotated source</div>
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<img id="annotated" class="hidden w-full rounded-xl border border-slate-800" />
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</div>
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</div>
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</section>
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</div>
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</main>
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<script>
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const file = document.getElementById('file');
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const go = document.getElementById('go');
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const crop = document.getElementById('crop');
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const annotated = document.getElementById('annotated');
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const meta = document.getElementById('meta');
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go.onclick = async () => {
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if (!file.files.length) return;
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const form = new FormData();
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form.append('file', file.files[0]);
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form.append('detector', document.getElementById('detector').value);
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form.append('buffer_ratio', document.getElementById('buffer_ratio').value);
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meta.textContent = 'Working...';
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const headers = {};
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const token = document.getElementById('auth_token').value.trim();
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if (token) headers['__AUTH_HEADER_NAME__'] = token;
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const resp = await fetch('/api/focus', { method: 'POST', body: form, headers });
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const data = await resp.json();
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if (!resp.ok) {
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meta.textContent = JSON.stringify(data, null, 2);
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return;
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}
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meta.textContent = JSON.stringify({
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filename: data.filename,
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detector: data.detector,
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method: data.method,
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buffer_ratio: data.buffer_ratio,
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detected_bbox: data.detected_bbox,
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square_bbox: data.square_bbox,
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source_size: data.source_size,
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}, null, 2);
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crop.src = data.crop_data_url;
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annotated.src = data.annotated_data_url;
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crop.classList.remove('hidden');
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annotated.classList.remove('hidden');
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};
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</script>
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</body>
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</html>
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""".replace("__AUTH_HEADER_NAME__", settings.auth_header_name)
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)
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@app.post("/api/focus")
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async def focus(
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request: Request,
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file: UploadFile = File(...),
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buffer_ratio: float = Form(0.15),
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detector: str = Form("subject"),
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_auth: None = Depends(require_auth),
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):
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from app.vision import process_image
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try:
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payload = await file.read()
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result = process_image(payload, file.filename or "upload", buffer_ratio=buffer_ratio, detector=detector)
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return {
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"filename": result["filename"],
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"detector": result["detector"],
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"method": result["method"],
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"buffer_ratio": result["buffer_ratio"],
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"detected_bbox": result["detected_bbox"],
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"square_bbox": result["square_bbox"],
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"source_size": result["source_size"],
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"crop_data_url": result["crop_data_url"],
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"annotated_data_url": result["annotated_data_url"],
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}
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except ValueError as exc:
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raise HTTPException(status_code=400, detail=str(exc)) from exc
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@app.post("/api/focus/image")
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async def focus_image(
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request: Request,
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file: UploadFile = File(...),
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buffer_ratio: float = Form(0.15),
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detector: str = Form("subject"),
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_auth: None = Depends(require_auth),
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):
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from app.vision import process_image
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try:
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payload = await file.read()
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result = process_image(payload, file.filename or "upload", buffer_ratio=buffer_ratio, detector=detector)
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return StreamingResponse(BytesIO(result["crop_bytes"]), media_type="image/jpeg")
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except ValueError as exc:
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raise HTTPException(status_code=400, detail=str(exc)) from exc
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