0052c59f81
Root cause: FileReader.readAsDataURL() loads the entire file into memory as a base64 string. With 50+ iPhone photos (3-12 MB each), this exceeds iOS Safari's per-tab memory limit and freezes the tab. Changes: - Replace readAsDataURL with URL.createObjectURL(file) — zero-copy file reference, no memory bloat (static/index.html) - Reduce batch size from 4 to 2 — gentler on memory-constrained devices - Add URL.revokeObjectURL() on reset — prevent blob URL leaks - Add HEIC/HEIF support to server.py — iPhone format compatibility Closes #1
318 lines
11 KiB
Python
318 lines
11 KiB
Python
"""EXIF + OCR test backend — validate that GPS survives upload pipeline."""
|
|
import io, json, re, uuid, sqlite3
|
|
from pathlib import Path
|
|
|
|
from fastapi import FastAPI, File, Form, HTTPException, UploadFile
|
|
from fastapi.staticfiles import StaticFiles
|
|
from PIL import Image as PILImage
|
|
|
|
# Optional HEIC/HEIF support for iPhone photos
|
|
try:
|
|
from pillow_heif import register_heif_opener
|
|
register_heif_opener()
|
|
HAS_HEIF = True
|
|
except ImportError:
|
|
HAS_HEIF = False
|
|
|
|
try:
|
|
import pytesseract
|
|
HAS_TESSERACT = True
|
|
except ImportError:
|
|
HAS_TESSERACT = False
|
|
|
|
UPLOADS = Path(__file__).parent / "uploads"
|
|
UPLOADS.mkdir(exist_ok=True)
|
|
CANTEEN_DB = Path(__file__).parent.parent / "canteen-asset-tracker" / "assets.db"
|
|
|
|
app = FastAPI(title="EXIF Test")
|
|
|
|
|
|
def _get_canteen_db():
|
|
"""Get a read/write connection to the canteen assets database."""
|
|
if not CANTEEN_DB.exists():
|
|
return None
|
|
conn = sqlite3.connect(str(CANTEEN_DB))
|
|
conn.row_factory = sqlite3.Row
|
|
return conn
|
|
|
|
|
|
def _dms_to_decimal(dms, ref):
|
|
"""Convert EXIF DMS tuple to decimal degrees."""
|
|
try:
|
|
deg, minutes, sec = float(dms[0]), float(dms[1]), float(dms[2])
|
|
decimal = deg + minutes / 60.0 + sec / 3600.0
|
|
if ref in ("S", "W"):
|
|
decimal = -decimal
|
|
return round(decimal, 7)
|
|
except Exception:
|
|
return None
|
|
|
|
|
|
def extract_exif(image_bytes: bytes) -> dict:
|
|
"""Pull all useful EXIF fields + GPS from raw image bytes."""
|
|
result = {"has_exif": False, "tags": {}, "gps": None}
|
|
try:
|
|
img = PILImage.open(io.BytesIO(image_bytes))
|
|
exif = img.getexif()
|
|
if not exif:
|
|
return result
|
|
|
|
for tag_id, value in exif.items():
|
|
tag_name = PILImage.ExifTags.TAGS.get(tag_id, f"0x{tag_id:04x}")
|
|
if tag_name in ("MakerNote", "UserComment", "PrintImageMatching"):
|
|
continue
|
|
result["tags"][tag_name] = str(value)[:300]
|
|
|
|
if result["tags"]:
|
|
result["has_exif"] = True
|
|
|
|
gps_ifd = exif.get_ifd(0x8825)
|
|
if gps_ifd:
|
|
lat_ref = gps_ifd.get(1, "N")
|
|
lat_dms = gps_ifd.get(2)
|
|
lng_ref = gps_ifd.get(3, "E")
|
|
lng_dms = gps_ifd.get(4)
|
|
|
|
if lat_dms and lng_dms:
|
|
lat = _dms_to_decimal(lat_dms, lat_ref)
|
|
lng = _dms_to_decimal(lng_dms, lng_ref)
|
|
if lat is not None and lng is not None:
|
|
result["gps"] = {
|
|
"lat": lat,
|
|
"lng": lng,
|
|
"lat_ref": str(lat_ref),
|
|
"lng_ref": str(lng_ref),
|
|
"raw_lat_dms": [float(v) for v in lat_dms],
|
|
"raw_lng_dms": [float(v) for v in lng_dms],
|
|
}
|
|
except Exception as e:
|
|
result["error"] = str(e)
|
|
|
|
return result
|
|
|
|
|
|
def run_ocr(image_bytes: bytes) -> dict:
|
|
"""Run Tesseract OCR on the image."""
|
|
if not HAS_TESSERACT:
|
|
return {"available": False, "text": "", "error": "pytesseract not installed"}
|
|
|
|
tmp_path = UPLOADS / f"ocr_{uuid.uuid4().hex}.jpg"
|
|
tmp_path.write_bytes(image_bytes)
|
|
try:
|
|
img = PILImage.open(tmp_path)
|
|
img_gray = img.convert("L")
|
|
text = pytesseract.image_to_string(img_gray, config="--psm 6")
|
|
match_5dash = re.search(r"(\d{5})[-\s]*(\d{6,})", text)
|
|
match_5plus = re.search(r"(\d{5,})", text)
|
|
return {
|
|
"available": True,
|
|
"raw_text": text.strip()[:500],
|
|
"match_5dash6": match_5dash.group(0) if match_5dash else None,
|
|
"match_5plus": match_5plus.group(0) if match_5plus else None,
|
|
}
|
|
finally:
|
|
tmp_path.unlink(missing_ok=True)
|
|
|
|
|
|
def lookup_machine_id(machine_id: str) -> dict | None:
|
|
"""Look up an asset by machine_id. Returns asset dict or None."""
|
|
conn = _get_canteen_db()
|
|
if not conn:
|
|
return None
|
|
try:
|
|
row = conn.execute(
|
|
"SELECT id, machine_id, name, category, status, address, building_name, "
|
|
"floor, room, latitude, longitude, make, model, description, photo_path "
|
|
"FROM assets WHERE machine_id = ?",
|
|
(machine_id.strip(),),
|
|
).fetchone()
|
|
if row:
|
|
return {
|
|
"id": row["id"],
|
|
"machine_id": row["machine_id"],
|
|
"name": row["name"],
|
|
"category": row["category"],
|
|
"status": row["status"],
|
|
"address": row["address"],
|
|
"building_name": row["building_name"],
|
|
"floor": row["floor"],
|
|
"room": row["room"],
|
|
"latitude": row["latitude"],
|
|
"longitude": row["longitude"],
|
|
"make": row["make"],
|
|
"model": row["model"],
|
|
"description": row["description"],
|
|
"photo_path": row["photo_path"],
|
|
}
|
|
finally:
|
|
conn.close()
|
|
return None
|
|
|
|
|
|
@app.post("/api/analyze")
|
|
async def analyze_photo(file: UploadFile = File(...)):
|
|
"""Upload a photo, get back EXIF + OCR results."""
|
|
contents = await file.read()
|
|
file_size = len(contents)
|
|
|
|
ext = Path(file.filename or "photo.jpg").suffix.lower()
|
|
if ext not in {".jpg", ".jpeg", ".png", ".webp", ".bmp", ".tiff", ".tif", ".dng", ".heic", ".heif"}:
|
|
ext = ".jpg"
|
|
fname = f"{uuid.uuid4().hex}{ext}"
|
|
(UPLOADS / fname).write_bytes(contents)
|
|
|
|
exif_result = extract_exif(contents)
|
|
ocr_result = run_ocr(contents) if HAS_TESSERACT else {"available": False, "text": ""}
|
|
|
|
machine_id = None
|
|
asset = None
|
|
if ocr_result.get("match_5dash6"):
|
|
machine_id = re.sub(r"\D", "", ocr_result["match_5dash6"])[-5:]
|
|
asset = lookup_machine_id(machine_id)
|
|
|
|
return {
|
|
"filename": file.filename,
|
|
"saved_as": fname,
|
|
"file_size": file_size,
|
|
"file_size_kb": round(file_size / 1024, 1),
|
|
"exif": exif_result,
|
|
"ocr": ocr_result,
|
|
"machine_id": machine_id,
|
|
"asset": asset,
|
|
}
|
|
|
|
|
|
@app.post("/api/bulk-process")
|
|
async def bulk_process(files: list[UploadFile] = File(...)):
|
|
"""Process multiple photos: OCR each, extract EXIF GPS, look up matching assets.
|
|
|
|
Returns a list of results, each with:
|
|
- filename, exif (gps), ocr match, matched asset (if found)
|
|
- needs_gps: true if asset exists AND has no coordinates AND photo has GPS
|
|
"""
|
|
if not files:
|
|
return {"results": [], "summary": {"total": 0, "has_gps": 0, "matched": 0, "needs_gps": 0}}
|
|
|
|
results = []
|
|
summary = {"total": len(files), "has_gps": 0, "matched": 0, "needs_gps": 0}
|
|
|
|
for file in files:
|
|
contents = await file.read()
|
|
file_size = len(contents)
|
|
|
|
# Save
|
|
ext = Path(file.filename or "photo.jpg").suffix.lower()
|
|
if ext not in {".jpg", ".jpeg", ".png", ".webp", ".bmp", ".tiff", ".tif", ".dng", ".heic", ".heif"}:
|
|
ext = ".jpg"
|
|
fname = f"{uuid.uuid4().hex}{ext}"
|
|
(UPLOADS / fname).write_bytes(contents)
|
|
|
|
exif_result = extract_exif(contents)
|
|
ocr_result = run_ocr(contents) if HAS_TESSERACT else {"available": False, "text": ""}
|
|
|
|
has_gps = exif_result.get("gps") is not None
|
|
if has_gps:
|
|
summary["has_gps"] += 1
|
|
|
|
machine_id = None
|
|
asset = None
|
|
needs_gps = False
|
|
|
|
if ocr_result.get("match_5dash6"):
|
|
machine_id = re.sub(r"\D", "", ocr_result["match_5dash6"])[-5:]
|
|
asset = lookup_machine_id(machine_id)
|
|
if asset:
|
|
summary["matched"] += 1
|
|
# Check if asset needs GPS
|
|
if (asset["latitude"] is None or asset["longitude"] is None) and has_gps:
|
|
needs_gps = True
|
|
summary["needs_gps"] += 1
|
|
|
|
results.append({
|
|
"filename": file.filename,
|
|
"saved_as": fname,
|
|
"file_size_kb": round(file_size / 1024, 1),
|
|
"exif": exif_result,
|
|
"ocr": ocr_result,
|
|
"machine_id": machine_id,
|
|
"asset": asset,
|
|
"needs_gps": needs_gps,
|
|
})
|
|
|
|
return {"results": results, "summary": summary}
|
|
|
|
|
|
@app.get("/api/lookup")
|
|
async def lookup_asset(machine_id: str = ""):
|
|
"""Look up an asset by machine_id in the canteen assets database."""
|
|
if not machine_id or not machine_id.strip():
|
|
return {"found": False, "reason": "No machine_id provided"}
|
|
|
|
asset = lookup_machine_id(machine_id.strip())
|
|
if asset:
|
|
return {"found": True, "asset": asset}
|
|
return {"found": False, "reason": f"No asset with machine_id '{machine_id}'"}
|
|
|
|
|
|
@app.post("/api/push-gps")
|
|
async def push_gps(request: dict):
|
|
"""Update an asset's GPS coordinates from photo EXIF data.
|
|
|
|
Body: {"asset_id": 123, "latitude": 40.7417, "longitude": -73.9292}
|
|
Only updates assets that currently have NULL lat/lng.
|
|
"""
|
|
asset_id = request.get("asset_id")
|
|
latitude = request.get("latitude")
|
|
longitude = request.get("longitude")
|
|
|
|
if not asset_id or latitude is None or longitude is None:
|
|
raise HTTPException(400, "asset_id, latitude, and longitude are required")
|
|
|
|
conn = _get_canteen_db()
|
|
if not conn:
|
|
raise HTTPException(500, "Database not available")
|
|
|
|
try:
|
|
# Only update if currently NULL
|
|
row = conn.execute(
|
|
"SELECT latitude, longitude FROM assets WHERE id = ?", (int(asset_id),)
|
|
).fetchone()
|
|
if not row:
|
|
conn.close()
|
|
raise HTTPException(404, f"Asset {asset_id} not found")
|
|
if row["latitude"] is not None and row["longitude"] is not None:
|
|
conn.close()
|
|
return {"updated": False, "reason": "Asset already has GPS coordinates", "asset_id": asset_id}
|
|
|
|
conn.execute(
|
|
"UPDATE assets SET latitude = ?, longitude = ?, updated_at = datetime('now') WHERE id = ?",
|
|
(float(latitude), float(longitude), int(asset_id)),
|
|
)
|
|
conn.commit()
|
|
conn.close()
|
|
return {"updated": True, "asset_id": asset_id, "latitude": float(latitude), "longitude": float(longitude)}
|
|
except Exception as e:
|
|
try:
|
|
conn.close()
|
|
except Exception:
|
|
pass
|
|
raise HTTPException(500, str(e))
|
|
|
|
|
|
@app.get("/api/uploads")
|
|
async def list_uploads():
|
|
"""List previously uploaded files."""
|
|
files = sorted(UPLOADS.glob("*"), key=lambda p: p.stat().st_mtime, reverse=True)
|
|
return [
|
|
{"name": f.name, "size_kb": round(f.stat().st_size / 1024, 1)}
|
|
for f in files[:20]
|
|
]
|
|
|
|
|
|
# Mount static LAST
|
|
app.mount("/", StaticFiles(directory="static", html=True), name="static")
|
|
|
|
if __name__ == "__main__":
|
|
import uvicorn
|
|
uvicorn.run(app, host="0.0.0.0", port=8903)
|