cleanup add training bell

backend/routes/api.py

@@ -90,9 +90,11 @@ def start_yolox_training():
         details_id = training.project_details_id
         
         # Step 1: Generate COCO JSON files
+        # IMPORTANT: Pass training_id (not details_id) so JSON files are generated
+        # in the same location where exp.py expects them
         from services.generate_json_yolox import generate_training_json
         print(f'Generating COCO JSON for training {training_id}...')
-        generate_training_json(details_id)
+        generate_training_json(training_id)
         
         # Step 2: Generate exp.py
         from services.generate_yolox_exp import save_yolox_exp
@@ -157,8 +159,9 @@ def start_yolox_training():
                 venv_activate = yolox_venv
             cmd = f'cmd /c ""{venv_activate}" && python tools\\train.py {train_args}"'
         else:
-            # Linux: Use bash with source
-            cmd = f'bash -c "source {yolox_venv} && python tools/train.py {train_args}"'
+            # Linux: Use bash with source to activate the venv
+            venv_activate = os.path.join(yolox_venv, 'bin', 'activate')
+            cmd = f'bash -c "source {venv_activate} && python tools/train.py {train_args}"'
         
         print(f'Training command: {cmd}')
         
@@ -496,17 +499,26 @@ def yolox_settings():
             settings['activation'] = settings['act']
             del settings['act']
         
-        # Type conversions
-        numeric_fields = [
-            'max_epoch', 'depth', 'width', 'warmup_epochs', 'warmup_lr', 
-            'no_aug_epochs', 'min_lr_ratio', 'weight_decay', 'momentum',
-            'print_interval', 'eval_interval', 'test_conf', 'nmsthre',
-            'multiscale_range', 'degrees', 'translate', 'shear',
-            'train', 'valid', 'test'
+        # Type conversions - Integer fields
+        integer_fields = [
+            'max_epoch', 'warmup_epochs', 'no_aug_epochs', 'print_interval', 
+            'eval_interval', 'multiscale_range', 'data_num_workers', 'num_classes'
         ]
         
-        for field in numeric_fields:
-            if field in settings:
+        for field in integer_fields:
+            if field in settings and settings[field] not in [None, '']:
+                settings[field] = int(float(settings[field]))  # Convert via float to handle "10.0" strings
+        
+        # Type conversions - Float fields
+        float_fields = [
+            'depth', 'width', 'warmup_lr', 'min_lr_ratio', 'weight_decay', 
+            'momentum', 'test_conf', 'nmsthre', 'degrees', 'translate', 
+            'shear', 'mosaic_prob', 'mixup_prob', 'hsv_prob', 'flip_prob',
+            'basic_lr_per_img', 'train', 'valid', 'test'
+        ]
+        
+        for field in float_fields:
+            if field in settings and settings[field] not in [None, '']:
                 settings[field] = float(settings[field])
         
         # Boolean conversions