148 lines
5.7 KiB
Python
148 lines
5.7 KiB
Python
from io import BytesIO
|
|
|
|
from fastapi import FastAPI, File, Form, HTTPException, UploadFile
|
|
from fastapi.responses import HTMLResponse, StreamingResponse
|
|
from app.config import settings
|
|
|
|
app = FastAPI(title="face-lock", version="0.2.0")
|
|
|
|
|
|
@app.get("/health")
|
|
def health():
|
|
return {"ok": True, "env": settings.env}
|
|
|
|
|
|
@app.get("/", response_class=HTMLResponse)
|
|
def index():
|
|
if settings.env != "dev":
|
|
return HTMLResponse("<h1>face-lock</h1><p>Set ENV=dev for the UI.</p>")
|
|
return HTMLResponse(
|
|
"""
|
|
<!doctype html>
|
|
<html lang="en">
|
|
<head>
|
|
<meta charset="utf-8" />
|
|
<meta name="viewport" content="width=device-width, initial-scale=1" />
|
|
<script src="https://cdn.tailwindcss.com"></script>
|
|
<title>face-lock</title>
|
|
</head>
|
|
<body class="bg-slate-950 text-slate-100 min-h-screen">
|
|
<main class="mx-auto max-w-6xl p-6">
|
|
<div class="mb-6">
|
|
<h1 class="text-3xl font-bold">face-lock</h1>
|
|
<p class="text-slate-400">Auto-detect the subject, square it up, and crop with buffer.</p>
|
|
</div>
|
|
<div class="grid gap-6 md:grid-cols-2">
|
|
<section class="rounded-2xl border border-slate-800 bg-slate-900 p-4">
|
|
<label class="block text-sm text-slate-400">Image</label>
|
|
<input id="file" type="file" accept="image/*" class="mt-2 block w-full rounded-lg border border-slate-700 bg-slate-950 p-3" />
|
|
<div class="mt-4 grid gap-4 sm:grid-cols-2">
|
|
<div>
|
|
<label class="block text-sm text-slate-400">Detector</label>
|
|
<select id="detector" class="mt-2 block w-full rounded-lg border border-slate-700 bg-slate-950 p-3">
|
|
<option value="auto">Auto</option>
|
|
<option value="face">Face</option>
|
|
<option value="person">Person</option>
|
|
<option value="salient">Subject</option>
|
|
</select>
|
|
</div>
|
|
<div>
|
|
<label class="block text-sm text-slate-400">Buffer ratio</label>
|
|
<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" />
|
|
</div>
|
|
</div>
|
|
<button id="go" class="mt-4 rounded-lg bg-cyan-500 px-4 py-2 font-semibold text-slate-950">Process</button>
|
|
<pre id="meta" class="mt-4 whitespace-pre-wrap rounded-lg bg-slate-950 p-3 text-xs text-slate-300"></pre>
|
|
</section>
|
|
<section class="rounded-2xl border border-slate-800 bg-slate-900 p-4">
|
|
<div class="mb-3 text-sm font-semibold text-slate-400">Result</div>
|
|
<div class="grid gap-4">
|
|
<div>
|
|
<div class="mb-2 text-xs uppercase tracking-wide text-slate-500">Crop</div>
|
|
<img id="crop" class="hidden w-full rounded-xl border border-slate-800" />
|
|
</div>
|
|
<div>
|
|
<div class="mb-2 text-xs uppercase tracking-wide text-slate-500">Annotated source</div>
|
|
<img id="annotated" class="hidden w-full rounded-xl border border-slate-800" />
|
|
</div>
|
|
</div>
|
|
</section>
|
|
</div>
|
|
</main>
|
|
<script>
|
|
const file = document.getElementById('file');
|
|
const go = document.getElementById('go');
|
|
const crop = document.getElementById('crop');
|
|
const annotated = document.getElementById('annotated');
|
|
const meta = document.getElementById('meta');
|
|
go.onclick = async () => {
|
|
if (!file.files.length) return;
|
|
const form = new FormData();
|
|
form.append('file', file.files[0]);
|
|
form.append('detector', document.getElementById('detector').value);
|
|
form.append('buffer_ratio', document.getElementById('buffer_ratio').value);
|
|
meta.textContent = 'Working...';
|
|
const resp = await fetch('/api/focus', { method: 'POST', body: form });
|
|
const data = await resp.json();
|
|
meta.textContent = JSON.stringify({
|
|
filename: data.filename,
|
|
detector: data.detector,
|
|
method: data.method,
|
|
buffer_ratio: data.buffer_ratio,
|
|
detected_bbox: data.detected_bbox,
|
|
square_bbox: data.square_bbox,
|
|
source_size: data.source_size,
|
|
}, null, 2);
|
|
crop.src = data.crop_data_url;
|
|
annotated.src = data.annotated_data_url;
|
|
crop.classList.remove('hidden');
|
|
annotated.classList.remove('hidden');
|
|
};
|
|
</script>
|
|
</body>
|
|
</html>
|
|
"""
|
|
)
|
|
|
|
|
|
@app.post("/api/focus")
|
|
async def focus(
|
|
file: UploadFile = File(...),
|
|
buffer_ratio: float = Form(0.15),
|
|
detector: str = Form("auto"),
|
|
):
|
|
from app.vision import process_image
|
|
|
|
try:
|
|
payload = await file.read()
|
|
result = process_image(payload, file.filename or "upload", buffer_ratio=buffer_ratio, detector=detector)
|
|
return {
|
|
"filename": result["filename"],
|
|
"detector": result["detector"],
|
|
"method": result["method"],
|
|
"buffer_ratio": result["buffer_ratio"],
|
|
"detected_bbox": result["detected_bbox"],
|
|
"square_bbox": result["square_bbox"],
|
|
"source_size": result["source_size"],
|
|
"crop_data_url": result["crop_data_url"],
|
|
"annotated_data_url": result["annotated_data_url"],
|
|
}
|
|
except ValueError as exc:
|
|
raise HTTPException(status_code=400, detail=str(exc)) from exc
|
|
|
|
|
|
@app.post("/api/focus/image")
|
|
async def focus_image(
|
|
file: UploadFile = File(...),
|
|
buffer_ratio: float = Form(0.15),
|
|
detector: str = Form("auto"),
|
|
):
|
|
from app.vision import process_image
|
|
|
|
try:
|
|
payload = await file.read()
|
|
result = process_image(payload, file.filename or "upload", buffer_ratio=buffer_ratio, detector=detector)
|
|
return StreamingResponse(BytesIO(result["crop_bytes"]), media_type=result["mime_type"])
|
|
except ValueError as exc:
|
|
raise HTTPException(status_code=400, detail=str(exc)) from exc
|