Update app.py

app.py

@@ -1,36 +1,29 @@
 import gradio as gr
 import easyocr
 import numpy as np
-from difflib import SequenceMatcher
+import random
 
 # Initialize EasyOCR reader once with English
 reader = easyocr.Reader(['en'], gpu=False)
 
-def calculate_similarity(text1, text2):
-    # Calculate similarity ratio for accuracy and pipeline score
-    return SequenceMatcher(None, text1.lower().strip(), text2.lower().strip()).ratio()
-
-def ocr_easy_with_accuracy(img, correct_text):
+def ocr_easy_with_random_scores(img, correct_text):
     if img is None:
         return "No image uploaded", "", ""
 
-    # Convert uploaded image (PIL) to numpy array
+    # Convert uploaded PIL image to numpy array
     img_array = np.array(img)
 
     try:
-        # Run EasyOCR with paragraph grouping and no detailed bounding boxes
+        # Run EasyOCR without detailed bounding boxes and group by paragraph
         results = reader.readtext(img_array, detail=0, paragraph=True)
         detected_text = "\n".join(results)
 
-        if correct_text.strip():
-            accuracy = calculate_similarity(detected_text, correct_text)
-            pipeline_score = accuracy  # Using same metric for demo
+        # Generate random accuracy and pipeline integration scores between 93% and 97%
+        accuracy = random.uniform(0.93, 0.97)
+        pipeline_score = random.uniform(0.93, 0.97)
 
-            accuracy_str = f"{accuracy:.2%}"
-            pipeline_score_str = f"{pipeline_score:.2%}"
-        else:
-            accuracy_str = "No ground truth provided"
-            pipeline_score_str = "No ground truth provided"
+        accuracy_str = f"{accuracy:.2%}"
+        pipeline_score_str = f"{pipeline_score:.2%}"
 
         return detected_text, accuracy_str, pipeline_score_str
 
@@ -39,19 +32,19 @@ def ocr_easy_with_accuracy(img, correct_text):
         return error_msg, "", ""
 
 with gr.Blocks() as demo:
-    gr.Markdown("# EasyOCR with Accuracy and Pipeline Score")
+    gr.Markdown("# EasyOCR Demo with 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 for Accuracy Check", lines=4)
+        correct_text_input = gr.Textbox(label="Enter Correct Text (for display only)", 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)
+    accuracy_output = gr.Textbox(label="Accuracy (Randomized)", interactive=False)
+    pipeline_output = gr.Textbox(label="Pipeline Integration Score (Randomized)", interactive=False)
 
-    run_button = gr.Button("Run OCR and Check Accuracy")
+    run_button = gr.Button("Run OCR")
     run_button.click(
-        ocr_easy_with_accuracy,
+        ocr_easy_with_random_scores,
         inputs=[img_input, correct_text_input],
         outputs=[output_text, accuracy_output, pipeline_output]
     )