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	Sped up ANPR
Sped up ANPR by only creating one ANPR instance, rather than initializing a new one every function call.
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							| @@ -12,6 +12,7 @@ torch.serialization.add_safe_globals(  # type: ignore | ||||
|     {"DetectionModel": DetectionModel}  # type: ignore | ||||
| ) | ||||
|  | ||||
| anpr = ANPR() | ||||
|  | ||||
| # Saving images locally | ||||
| UPLOAD_FOLDER = "uploads" | ||||
| @@ -32,7 +33,7 @@ def data(): | ||||
|     with open("image.jpg", "wb") as f: | ||||
|         f.write(data) | ||||
|  | ||||
|     status = asyncio.run(process_image("image.jpg")) | ||||
|     status = asyncio.run(process_image(file="image.jpg", anpr=anpr)) | ||||
|     return jsonify( | ||||
|         { | ||||
|             "message": "Image sent succesfully", | ||||
| @@ -41,9 +42,8 @@ def data(): | ||||
|     ) | ||||
|  | ||||
|  | ||||
| async def process_image(file: str) -> bool: | ||||
| async def process_image(file: str, anpr: ANPR) -> bool: | ||||
|     print("Processing image") | ||||
|     anpr = ANPR() | ||||
|     anpr_info = await anpr.detect(file)  # type: ignore | ||||
|     number_plate = anpr_info["plate_number"] | ||||
|     if number_plate: | ||||
|   | ||||
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