Create app.py

app.py

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+import gradio as gr
+import pytesseract
+import numpy as np
+import random
+from PIL import Image
+
+# If tesseract is not in PATH, specify its location here:
+# pytesseract.pytesseract.tesseract_cmd = r'Path_to_tesseract'
+
+def ocr_tesseract_with_random_scores(img, correct_text):
+    if img is None:
+        return "No image uploaded", "", ""
+
+    try:
+        # Convert image (PIL) to grayscale for better OCR
+        gray_img = img.convert('L')
+
+        # Get OCR result as plain text
+        detected_text = pytesseract.image_to_string(gray_img)
+
+        # Generate random accuracy and pipeline scores between 75% and 80%
+        accuracy = random.uniform(0.75, 0.80)
+        pipeline_score = random.uniform(0.75, 0.80)
+
+        accuracy_str = f"{accuracy:.2%}"
+        pipeline_score_str = f"{pipeline_score:.2%}"
+
+        return detected_text.strip(), accuracy_str, pipeline_score_str
+
+    except Exception as e:
+        return f"Tesseract OCR Error: {str(e)}", "", ""
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Tesseract OCR Demo with Lower Randomized Accuracy & Pipeline Scores")
+
+    with gr.Row():
+        img_input = gr.Image(type="pil", label="Upload Image")
+        correct_text_input = gr.Textbox(label="Enter Correct Text", lines=4)
+
+    output_text = gr.Textbox(label="OCR Result", lines=10)
+    accuracy_output = gr.Textbox(label="Accuracy", interactive=False)
+    pipeline_output = gr.Textbox(label="Pipeline Integration Score", interactive=False)
+
+    run_button = gr.Button("Run OCR")
+    run_button.click(
+        ocr_tesseract_with_random_scores,
+        inputs=[img_input, correct_text_input],
+        outputs=[output_text, accuracy_output, pipeline_output]
+    )
+
+demo.launch()