ChronoStellar commited on
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dfbcd08
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1 Parent(s): 87de308

Update app.py

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Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -14,9 +14,9 @@ from PIL import Image
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  # Paths to your models
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  MODEL_TYPES = ["HOG & Logistic Regression","CRNN CTC","Fine Tuned TrOCR"]
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- clf_hog = joblib.load('/content/HOG_LogRes.pkl')
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- clf_crnn = tf.keras.models.load_model('/content/crnn_ctc.keras')
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  num_to_char = joblib.load('./decoder.joblib')
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  processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-printed")
@@ -109,8 +109,8 @@ interface = gr.Interface(
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  title="Automatic License Plate Recognition",
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  description="Provide the file path of a license plate image, choose a model, and the system will predict the text on it. These Models are all trained on the same dataset, one model might be better compared to the other",
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  examples=[
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- ['/content/B8837NR.jpg', ''],
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- ['/content/E5105OD.jpg', '']
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  ]
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  )
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  # Paths to your models
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  MODEL_TYPES = ["HOG & Logistic Regression","CRNN CTC","Fine Tuned TrOCR"]
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+ clf_hog = joblib.load('./HOG_LogRes.pkl')
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+ clf_crnn = tf.keras.models.load_model('./crnn_ctc.keras')
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  num_to_char = joblib.load('./decoder.joblib')
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  processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-printed")
 
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  title="Automatic License Plate Recognition",
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  description="Provide the file path of a license plate image, choose a model, and the system will predict the text on it. These Models are all trained on the same dataset, one model might be better compared to the other",
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  examples=[
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+ ['./B8837NR.jpg', 'Fine Tuned TrOCR'],
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+ ['./E5105OD.jpg', 'Fine Tuned TrOCR']
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  ]
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  )
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