Delete app.py

app.py

@@ -1,76 +0,0 @@
-import gradio as gr
-import numpy as np
-#from transformers import TrOCRProcessor, VisionEncoderDecoderModel
-from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering
-from PIL import Image
-
-#client = InferenceClient("models/microsoft/trocr-base-handwritten")
-processor = AutoProcessor.from_pretrained("Sharka/CIVQA_LayoutLMv2_EasyOCR")
-model = AutoModelForDocumentQuestionAnswering.from_pretrained("Sharka/CIVQA_LayoutLMv2_EasyOCR")
-
-def sepia(input_img):
-    sepia_filter = np.array([
-        [0.393, 0.769, 0.189],
-        [0.349, 0.686, 0.168],
-        [0.272, 0.534, 0.131]
-    ])
-    sepia_img = input_img.dot(sepia_filter.T)
-    sepia_img /= sepia_img.max()
-    sepia_values = repr(sepia_img)
-    return sepia_img, sepia_values
-
-
-## https://www.gradio.app/docs/gradio/blocks
-## required positional arguments: 'inputs' and 'outputs'
-def process_image(image):
-    try:
-        pixel_values = processor(images=image, return_tensors="pt").pixel_values
-        
-        generated_ids = model.generate(pixel_values)
-        generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
-        return generated_text
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-def additional_input(text):
-    return f"Additional input received: {text}"
-
-sepia_interface = gr.Interface(sepia, gr.Image(), "image")
-
-with gr.Blocks() as generated_output:
-    with gr.Column():
-        sepia_values_text=gr.Textbox(label="Sepia Values")
-        output_img = gr.Image(label="Output Image")
-        gr.Interface(fn=sepia,
-                    inputs=gr.Image(
-                        #this makes the camera stream live
-                        sources=["webcam"], 
-                        streaming=True
-                    ), 
-                    outputs=[output_img, sepia_values_text],
-                    live=True,
-                    show_progress="full")
-    with gr.Row():
-        output_img.change(
-            fn=process_image,
-            inputs=output_img,
-            outputs=gr.Textbox(label="Recognized Text"),
-            show_progress="full")
-#with gr.Blocks() as generated_output:
-#    inp = gr.Interface(sepia, gr.Image(), "image")
-#    out = gr.Textbox()
-
-
-#demo = gr.TabbedInterface([sepia_interface, generated_output], ["RGB Sepia Filter", "Handwritten to Text"])
-
-#with gr.Blocks() as demo:
-#    with gr.Row():
-#        input_img = gr.Image(label="Input Image")
-#        submit_button = gr.Button("Submit")
-#        output_img = gr.Image(label="Output Image")
-#        sepia_values_text = gr.Textbox(label="Sepia Values")
-
-#    submit_button.click(sepia, inputs=input_img, outputs=[output_img, sepia_values_text])
-    
-if __name__ == "__main__":
-    generated_output.launch()