A backup of current application file.

app.py.bak

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+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()