move/remove mtcnn initialization appropriately
Browse files- app.py +2 -3
- object_detection.py +0 -3
app.py
CHANGED
@@ -40,6 +40,8 @@ result_queue: "queue.Queue[List[Detection]]" = queue.Queue()
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# Appropriate imports needed for analysis
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# Initialize the Hugging Face pipeline for facial emotion detection
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emotion_pipeline = pipeline("image-classification",
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@@ -157,9 +159,6 @@ logging.getLogger("streamlit").setLevel(logging.ERROR)
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# Container to hold image data and analysis results
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img_container = {"input": None, "analyzed": None, "analysis_time": None}
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# Initialize MTCNN for face detection
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mtcnn = MTCNN()
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-
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# Logger for debugging and information
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logger = logging.getLogger(__name__)
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# Appropriate imports needed for analysis
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# Initialize MTCNN for face detection
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mtcnn = MTCNN()
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# Initialize the Hugging Face pipeline for facial emotion detection
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emotion_pipeline = pipeline("image-classification",
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# Container to hold image data and analysis results
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img_container = {"input": None, "analyzed": None, "analysis_time": None}
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# Logger for debugging and information
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logger = logging.getLogger(__name__)
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object_detection.py
CHANGED
@@ -192,9 +192,6 @@ logging.getLogger("streamlit").setLevel(logging.ERROR)
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# Container to hold image data and analysis results
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img_container = {"input": None, "analyzed": None, "analysis_time": None}
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# Initialize MTCNN for face detection
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mtcnn = MTCNN()
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-
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# Logger for debugging and information
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logger = logging.getLogger(__name__)
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# Container to hold image data and analysis results
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img_container = {"input": None, "analyzed": None, "analysis_time": None}
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# Logger for debugging and information
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logger = logging.getLogger(__name__)
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