new index____

main.py

@@ -48,6 +48,9 @@ app = Flask(__name__)
 # Use the new upload directory
 UPLOAD_FOLDER = upload_dir  # Changed from 'uploads' to upload_dir
 
+if not os.path.exists('ans_image'):
+    os.makedirs('ans_image')
+
 @app.route('/')
 def index():
     return render_template('index.html')
@@ -117,50 +120,79 @@ def compute_answers():
 @app.route('/compute_marks', methods=['POST'])
 def compute_marks():
     try:
-        # Get answers
+        # Get answers from frontend
         a = request.form.get('answers')
         if not a:
             return jsonify({"error": "No answers provided"}), 400
         
         print("Received answers:", a)
         
+        # Parse answers
         a = json.loads(a)
         answers = []
         for i in a:
             ans = i.split('\n\n')
             answers.append(ans)
         
-        # Process student folders and files
-        data = {}
-        parent_folder = "ans_image"  # Your main folder
+        print("Processed answers:", answers)
+
+        # Create vectors for reference answers first
+        sen_vec_answers = []
+        word_vec_answers = []
+        for answer_set in answers:
+            temp_v = []
+            temp_w = []
+            for ans in answer_set:
+                temp_v.append(question_vector_sentence(ans))
+                temp_w.append(question_vector_word(ans))
+            sen_vec_answers.append(temp_v)
+            word_vec_answers.append(temp_w)
         
-        # Check if parent folder exists
-        if not os.path.exists(parent_folder):
-            return jsonify({"error": "ans_image folder not found"}), 400
+        # Process uploaded files
+        files = request.files.getlist('files[]')
+        if not files:
+            return jsonify({"error": "No files uploaded"}), 400
             
-        # Process each student folder
-        for student_folder in os.listdir(parent_folder):
-            student_path = os.path.join(parent_folder, student_folder)
-            if os.path.isdir(student_path):
-                data[student_folder] = []
-                # Get all images in student folder
-                for image_file in sorted(os.listdir(student_path)):
-                    if image_file.endswith(('.jpg', '.jpeg', '.png')):
-                        image_path = os.path.join(student_path, image_file)
-                        image_name = os.path.splitext(image_file)[0]  # Get filename without extension
-                        data[student_folder].append({
-                            'path': image_path,
-                            'name': image_name
-                        })
-
-        # Calculate marks
+        data = {}
+        # Process and save uploaded files
+        for file in files:
+            if file.filename.endswith(('.jpg', '.jpeg', '.png')):
+                # Get the relative path and normalize it
+                relative_path = file.filename.replace('\\', '/')
+                path_parts = relative_path.split('/')
+                
+                if len(path_parts) >= 2:
+                    student_folder = path_parts[1]  # Get the student folder name
+                    
+                    # Save file in ans_image directory
+                    save_dir = os.path.join('ans_image', student_folder)
+                    os.makedirs(save_dir, exist_ok=True)
+                    
+                    save_path = os.path.join(save_dir, path_parts[-1])
+                    file.save(save_path)
+                    save_path = save_path.replace('\\', '/')
+                    
+                    # Store file info in data dictionary
+                    if student_folder not in data:
+                        data[student_folder] = []
+                    data[student_folder].append({
+                        'path': save_path,
+                        'name': os.path.splitext(path_parts[-1])[0]  # filename without extension
+                    })
+
+        print("Processed files structure:", data)
+
+        # Calculate marks for each student and image
         results = []
         for student_folder, images in data.items():
             for idx, image_info in enumerate(images):
                 try:
+                    # Extract text from image
                     image_path = image_info['path']
                     s_answer = extract_text_from_image(image_path)
-                    
+                    print(f"Extracted answer from {image_path}:", s_answer)
+
+                    # Calculate marks
                     if idx < len(answers):  # Make sure we have corresponding answer
                         tf_idf_word_values, max_tfidf = create_tfidf_values(answers[idx])
                         m = marks(s_answer, sen_vec_answers[idx], word_vec_answers[idx], 
@@ -168,18 +200,18 @@ def compute_marks():
                         
                         if isinstance(m, torch.Tensor):
                             m = m.item()
-                            
-                        results.append({
-                            'student': student_folder,
-                            'image_name': image_info['name'],
-                            'marks': round(m, 2)
-                        })
+                        
+                        mark_value = round(float(m), 2)
                     else:
-                        results.append({
-                            'student': student_folder,
-                            'image_name': image_info['name'],
-                            'marks': 0
-                        })
+                        mark_value = 0
+
+                    results.append({
+                        'student': student_folder,
+                        'image_name': image_info['name'],
+                        'marks': mark_value
+                    })
+                    print(f"Marks for {student_folder}/{image_info['name']}: {mark_value}")
+
                 except Exception as e:
                     print(f"Error processing {image_path}: {str(e)}")
                     results.append({
@@ -188,6 +220,7 @@ def compute_marks():
                         'marks': 0
                     })
 
+        print("Final results:", results)
         return jsonify({"message": results}), 200
 
     except Exception as e: