Update docs predict, buttons, reference (#6585)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

ultralytics/cfg/__init__.py

@@ -71,8 +71,8 @@ CFG_INT_KEYS = ('epochs', 'patience', 'batch', 'workers', 'seed', 'close_mosaic'
                 'line_width', 'workspace', 'nbs', 'save_period')
 CFG_BOOL_KEYS = ('save', 'exist_ok', 'verbose', 'deterministic', 'single_cls', 'rect', 'cos_lr', 'overlap_mask', 'val',
                  'save_json', 'save_hybrid', 'half', 'dnn', 'plots', 'show', 'save_txt', 'save_conf', 'save_crop',
-                 'show_labels', 'show_conf', 'visualize', 'augment', 'agnostic_nms', 'retina_masks', 'boxes', 'keras',
-                 'optimize', 'int8', 'dynamic', 'simplify', 'nms', 'profile')
+                 'show_labels', 'show_conf', 'visualize', 'augment', 'agnostic_nms', 'retina_masks', 'show_boxes',
+                 'keras', 'optimize', 'int8', 'dynamic', 'simplify', 'nms', 'profile')
 
 
 def cfg2dict(cfg):
@@ -164,6 +164,9 @@ def _handle_deprecation(custom):
     """Hardcoded function to handle deprecated config keys."""
 
     for key in custom.copy().keys():
+        if key == 'boxes':
+            deprecation_warn(key, 'show_boxes')
+            custom['show_boxes'] = custom.pop('boxes')
         if key == 'hide_labels':
             deprecation_warn(key, 'show_labels')
             custom['show_labels'] = custom.pop('hide_labels') == 'False'

ultralytics/cfg/default.yaml

@@ -49,25 +49,27 @@ iou: 0.7  # (float) intersection over union (IoU) threshold for NMS
 max_det: 300  # (int) maximum number of detections per image
 half: False  # (bool) use half precision (FP16)
 dnn: False  # (bool) use OpenCV DNN for ONNX inference
-plots: True  # (bool) save plots during train/val
+plots: True  # (bool) save plots and images during train/val
 
-# Prediction settings --------------------------------------------------------------------------------------------------
+# Predict settings -----------------------------------------------------------------------------------------------------
 source:  # (str, optional) source directory for images or videos
-show: False  # (bool) show results if possible
-save_txt: False  # (bool) save results as .txt file
-save_conf: False  # (bool) save results with confidence scores
-save_crop: False  # (bool) save cropped images with results
-show_labels: True  # (bool) show object labels in plots
-show_conf: True  # (bool) show object confidence scores in plots
 vid_stride: 1  # (int) video frame-rate stride
 stream_buffer: False  # (bool) buffer all streaming frames (True) or return the most recent frame (False)
-line_width:   # (int, optional) line width of the bounding boxes, auto if missing
 visualize: False  # (bool) visualize model features
 augment: False  # (bool) apply image augmentation to prediction sources
 agnostic_nms: False  # (bool) class-agnostic NMS
 classes:  # (int | list[int], optional) filter results by class, i.e. classes=0, or classes=[0,2,3]
 retina_masks: False  # (bool) use high-resolution segmentation masks
-boxes: True  # (bool) Show boxes in segmentation predictions
+
+# Visualize settings ---------------------------------------------------------------------------------------------------
+show: False  # (bool) show predicted images and videos if environment allows
+save_txt: False  # (bool) save results as .txt file
+save_conf: False  # (bool) save results with confidence scores
+save_crop: False  # (bool) save cropped images with results
+show_labels: True  # (bool) show prediction labels, i.e. 'person'
+show_conf: True  # (bool) show prediction confidence, i.e. '0.99'
+show_boxes: True  # (bool) show prediction boxes
+line_width:   # (int, optional) line width of the bounding boxes. Scaled to image size if None.
 
 # Export settings ------------------------------------------------------------------------------------------------------
 format: torchscript  # (str) format to export to, choices at https://docs.ultralytics.com/modes/export/#export-formats

ultralytics/engine/predictor.py

@@ -170,7 +170,7 @@ class BasePredictor:
         if self.args.save or self.args.show:  # Add bbox to image
             plot_args = {
                 'line_width': self.args.line_width,
-                'boxes': self.args.boxes,
+                'boxes': self.args.show_boxes,
                 'conf': self.args.show_conf,
                 'labels': self.args.show_labels}
             if not self.args.retina_masks: