Update app.py

app.py

@@ -24,7 +24,6 @@ roberta_model = AutoModelForMaskedLM.from_pretrained("roberta-large").to(device)
 print(f'TrOCR and YOLO Models loaded on {device}')
 
 
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 CONFIDENCE_THRESHOLD = 0.72
@@ -145,7 +144,6 @@ def inference(image_path, debug=False, return_texts='final'):
 # image_path = "raw_dataset/g06-037h.png"
 df, bounding_path, tokens, logits, gen_texts = inference(image_path, debug=False, return_texts='final_v2')
 
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 def get_new_logits(tokens):
@@ -174,7 +172,6 @@ for i, j in zip(indices[0], indices[1]):
 new_logits = get_new_logits(tokens)
 
 
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 for i, j in zip(indices[0], indices[1]):
@@ -184,7 +181,7 @@ logits_flattened = slogits.reshape(-1, slogits.shape[-1])
 processor.batch_decode([logits_flattened.argmax(-1)], skip_special_tokens=True)
 
 
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+
 
 
 def gradio_inference(image_path):