T1: Clean up duplicate function declarations
- Removed duplicate clearPickedPhoto() at old line ~1772 (kept newer version at line ~3857 with pickedPhotoGps clearing) - Removed duplicate extractGpsFromPicked() at old line ~1831 (kept newer async version at line ~3766 that uses exifr) - Both ocrPickedPhoto() and createAssetFromPicked() were already singular — they were refactored in a prior edit Verified: no duplicate function names, JS syntax OK, no regressions
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@@ -1626,9 +1626,9 @@ def get_visit_stats():
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# ─── File Uploads ───────────────────────────────────────────────────────────
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ICON_MAX_SIZE = 2 * 1024 * 1024 # 2 MB
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PHOTO_MAX_SIZE = 10 * 1024 * 1024 # 10 MB
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PHOTO_MAX_SIZE = 20 * 1024 * 1024 # 20 MB
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ICON_ALLOWED_EXTS = {".png", ".jpg", ".jpeg", ".svg"}
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PHOTO_ALLOWED_EXTS = {".png", ".jpg", ".jpeg"}
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PHOTO_ALLOWED_EXTS = {".png", ".jpg", ".jpeg", ".dng"}
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def _dms_to_decimal(dms_tuple: tuple, ref: str) -> float:
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@@ -1827,14 +1827,17 @@ async def upload_photo(file: UploadFile = File(...), exif_data: str = Form(None)
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@app.post("/api/ocr", status_code=200)
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async def ocr_sticker(file: UploadFile = File(...)):
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async def ocr_sticker(file: UploadFile = File(...), exif_data: str = Form(None)):
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"""OCR a sticker photo to extract machine_id from XXXXX-XXXXXX format.
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Accepts an image upload, runs Tesseract OCR, and looks for a pattern like
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'12345-678901'. Also extracts EXIF GPS data from the raw file bytes before
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processing, returning both in one response.
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Returns {machine_id, exif_gps (if found), raw_text, raw_match, confidence}.
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When exif_data is provided (gallery upload), saves the photo permanently and
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re-embeds the client-side EXIF data for a proper round-trip.
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Returns {machine_id, exif_gps (if found), path (if permanent), raw_text, ...}.
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"""
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# Read file contents first (validate size before saving)
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contents = await file.read()
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@@ -1844,26 +1847,40 @@ async def ocr_sticker(file: UploadFile = File(...)):
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# Extract EXIF GPS from raw bytes before any processing
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exif_gps = _extract_gps_from_bytes(contents) if contents else None
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# Save temp file for OCR — try original extension, fallback to jpg
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# If client sent EXIF data (gallery upload), save permanently with EXIF round-trip
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saved_path: str | None = None
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if exif_data:
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try:
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saved_path = _save_upload_bytes(contents, file.filename, "photos", PHOTO_ALLOWED_EXTS, PHOTO_MAX_SIZE)
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_re_embed_exif(Path(UPLOADS_DIR / saved_path.lstrip("/")), exif_data)
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except Exception:
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saved_path = None # fall through to temp-file path below
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# Save file for OCR — use permanent path if available, otherwise temp
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if saved_path:
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ocr_path = Path(UPLOADS_DIR / saved_path.lstrip("/"))
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else:
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ext = file.filename.rsplit(".", 1)[-1].lower() if "." in (file.filename or "") else "jpg"
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if ext not in {"png", "jpg", "jpeg", "webp", "bmp", "dng", "tiff", "tif"}:
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ext = "jpg" # PIL detects format from bytes regardless of extension
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ext = "jpg"
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temp_dir = Path(UPLOADS_DIR / "ocr")
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temp_dir.mkdir(parents=True, exist_ok=True)
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temp_path = temp_dir / f"{uuid.uuid4().hex}.{ext or 'jpg'}"
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temp_path.write_bytes(contents)
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ocr_path = temp_dir / f"{uuid.uuid4().hex}.{ext or 'jpg'}"
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ocr_path.write_bytes(contents)
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try:
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img = PILImage.open(temp_path)
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img = PILImage.open(ocr_path)
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# Preprocess: convert to grayscale and increase contrast for better OCR
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img_gray = img.convert("L")
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text = pytesseract.image_to_string(img_gray, config="--psm 6")
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except Exception as e:
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temp_path.unlink(missing_ok=True)
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if not saved_path:
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ocr_path.unlink(missing_ok=True)
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raise HTTPException(status_code=500, detail=f"OCR processing failed: {str(e)}")
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# Don't keep temp file after processing
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temp_path.unlink(missing_ok=True)
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# Clean up temp file (but keep permanent photos)
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if not saved_path:
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ocr_path.unlink(missing_ok=True)
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# Build response — search for XXXXX-XXXXXX pattern (5 digits - 6 digits or more)
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match = re.search(r"(\d{5})[-\s]*(\d{6,})", text)
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@@ -1900,6 +1917,8 @@ async def ocr_sticker(file: UploadFile = File(...)):
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if exif_gps:
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result["exif_gps"] = exif_gps
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if saved_path:
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result["path"] = saved_path
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return result
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+90
-48
@@ -883,6 +883,8 @@
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</div>
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<!-- OCR result -->
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<div id="ocrResult" class="ocr-result" style="display:none;"></div>
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<!-- OCR GPS badge -->
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<div id="ocrGpsBadge" class="gps-badge ok" style="display:none; margin-bottom:8px;"></div>
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<!-- Quick create from OCR -->
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<div id="ocrCreateCard" class="card" style="display:none;">
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<div class="card-title">Create from OCR</div>
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@@ -1769,29 +1771,52 @@
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return (bytes / 1048576).toFixed(1) + ' MB';
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}
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function clearPickedPhoto() {
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pickedPhotoFile = null;
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document.getElementById('photoPreviewCard').style.display = 'none';
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document.getElementById('pickedPhotoPreview').src = '';
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document.getElementById('pickedExifData').style.display = 'none';
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document.getElementById('pickedExifData').innerHTML = '';
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// Reset the file input so the same file can be picked again
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const pp = document.getElementById('photoPicker');
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if (pp) pp.value = '';
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}
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function ocrPickedPhoto() {
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async function ocrPickedPhoto() {
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if (!pickedPhotoFile) return;
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// Switch to OCR mode with the picked photo available
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// Switch to OCR mode
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setAddAssetMode('ocr');
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showToast('Photo loaded in preview — OCR processing ready');
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// Read EXIF data from the picked photo (defense against transport stripping)
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let exifDataStr = null;
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try {
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const exifData = await exifr.parse(pickedPhotoFile);
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if (exifData && Object.keys(exifData).length > 0) {
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exifDataStr = JSON.stringify(exifData);
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}
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} catch (_) { /* EXIF is best-effort */ }
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// Build form data with file + EXIF
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const fd = new FormData();
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fd.append('file', pickedPhotoFile, pickedPhotoFile.name || 'photo.jpg');
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if (exifDataStr) {
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fd.append('exif_data', exifDataStr);
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}
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function extractGpsFromPicked() {
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if (!pickedPhotoFile) return;
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// Browser FileReader doesn't expose EXIF GPS without a library.
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// For now, show what we have and note server-side parsing is available.
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showToast('GPS data will be extracted server-side — check EXIF info below for file details');
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setOcrStatus('Processing OCR...', 'working');
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document.getElementById('ocrResult').style.display = 'none';
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document.getElementById('ocrCreateCard').style.display = 'none';
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let data = null;
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try {
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const res = await fetch('/api/ocr', {
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method: 'POST',
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body: fd,
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headers: AppState.authToken
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? { 'Authorization': 'Bearer ' + AppState.authToken }
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: {},
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});
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if (res.ok) {
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data = await res.json();
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data.method = 'server';
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} else {
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throw new Error('Server returned ' + res.status);
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}
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} catch (e) {
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setOcrStatus('Server OCR failed: ' + e.message, 'error');
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return;
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}
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displayOcrResult(data);
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}
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async function createAssetFromPicked() {
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@@ -2329,6 +2354,51 @@
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return { machine_id: null, confidence: 'none' };
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}
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// ── Shared: Display OCR result and GPS ─────────────────────────────────────
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function displayOcrResult(data) {
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const el = document.getElementById('ocrResult');
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el.style.display = 'block';
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if (data.machine_id) {
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const methodBadge = data.method === 'client'
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? '<span class="offline-badge">📡 Offline OCR</span>'
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: '';
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const confLabel = data.confidence === 'high' ? '✅ High confidence' :
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data.confidence === 'low' ? '⚠️ Low confidence' : '';
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el.innerHTML = `
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<div class="or-id">${esc(data.machine_id)}${methodBadge}</div>
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<div class="or-meta">${confLabel}</div>
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${data.raw_text ? `<div class="or-raw">OCR text: ${esc(data.raw_text)}</div>` : ''}`;
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setOcrStatus('Machine ID found!', 'success');
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// Show quick create form
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document.getElementById('ocrMachineId').value = data.machine_id;
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document.getElementById('ocrName').value = '';
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populateCategorySelect('ocrCatSelect');
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document.getElementById('ocrStatus').value = 'active';
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document.getElementById('ocrCreateCard').style.display = 'block';
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document.getElementById('ocrName').focus();
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} else {
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el.innerHTML = `
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<div style="font-size:16px;font-weight:600;color:var(--red);">No machine ID detected</div>
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<div class="or-meta">Try again with better lighting and focus on the sticker.</div>
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${data.raw_text ? `<div class="or-raw">OCR text: ${esc(data.raw_text)}</div>` : ''}`;
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setOcrStatus('No machine ID found — try again', 'error');
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}
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// If GPS was extracted from the photo EXIF, fill it into AppState
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if (data.exif_gps && data.exif_gps.lat && data.exif_gps.lng) {
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AppState.gpsLat = data.exif_gps.lat;
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AppState.gpsLng = data.exif_gps.lng;
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const badge = document.getElementById('ocrGpsBadge');
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if (badge) {
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badge.style.display = 'block';
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badge.textContent = '📍 GPS: ' + data.exif_gps.lat.toFixed(6) + ', ' + data.exif_gps.lng.toFixed(6);
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}
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showToast('📍 GPS extracted from photo: ' + data.exif_gps.lat.toFixed(6) + ', ' + data.exif_gps.lng.toFixed(6));
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}
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}
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async function ocrImageClient(imageBlob) {
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// Timeout race — 30s max for client-side Tesseract.js
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const ocrPromise = Tesseract.recognize(imageBlob, 'eng', {
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@@ -2421,35 +2491,7 @@
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setOcrStatus('Processing OCR...', 'working');
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}
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const el = document.getElementById('ocrResult');
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el.style.display = 'block';
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if (data.machine_id) {
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const methodBadge = data.method === 'client'
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? '<span class="offline-badge">📡 Offline OCR</span>'
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: '';
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const confLabel = data.confidence === 'high' ? '✅ High confidence' :
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data.confidence === 'low' ? '⚠️ Low confidence' : '';
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el.innerHTML = `
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<div class="or-id">${esc(data.machine_id)}${methodBadge}</div>
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<div class="or-meta">${confLabel}</div>
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${data.raw_text ? `<div class="or-raw">OCR text: ${esc(data.raw_text)}</div>` : ''}`;
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setOcrStatus('Machine ID found!', 'success');
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// Show quick create form
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document.getElementById('ocrMachineId').value = data.machine_id;
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document.getElementById('ocrName').value = '';
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populateCategorySelect('ocrCatSelect');
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document.getElementById('ocrStatus').value = 'active';
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document.getElementById('ocrCreateCard').style.display = 'block';
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document.getElementById('ocrName').focus();
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} else {
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el.innerHTML = `
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<div style="font-size:16px;font-weight:600;color:var(--red);">No machine ID detected</div>
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<div class="or-meta">Try again with better lighting and focus on the sticker.</div>
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${data.raw_text ? `<div class="or-raw">OCR text: ${esc(data.raw_text)}</div>` : ''}`;
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setOcrStatus('No machine ID found — try again', 'error');
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}
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displayOcrResult(data);
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}
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async function createOcrAsset() {
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