Boost parameters

inference.py

@@ -237,7 +237,7 @@ def format_predictions(image_shapes, outputs, width, height, gp=None, batch_size
          
     return all_preds, real_width, real_height
 
-def do_confidence_boost(inference, safe_preds, gp=None, batch_size=BATCH_SIZE, verbose=True):
+def do_confidence_boost(inference, safe_preds, gp=None, batch_size=BATCH_SIZE, conf_power=1, conf_decay=1, verbose=True):
     """
     Args:
         frames_dir: a directory containing frames to be evaluated
@@ -275,7 +275,7 @@ def do_confidence_boost(inference, safe_preds, gp=None, batch_size=BATCH_SIZE, v
                     next_frame = inference[batch_i + 1][0]
 
                 if next_frame != None:
-                    boost_frame(safe_frame, next_frame, 1)
+                    boost_frame(safe_frame, next_frame, 1, decay=conf_decay)
 
                 prev_frame = None
                 if i-1 >= 0:
@@ -284,18 +284,18 @@ def do_confidence_boost(inference, safe_preds, gp=None, batch_size=BATCH_SIZE, v
                     prev_frame = inference[batch_i - 1][len(inference[batch_i - 1]) - 1]
 
                 if prev_frame != None:
-                    boost_frame(safe_frame, prev_frame, -1)
+                    boost_frame(safe_frame, prev_frame, -1, power=conf_power, decay=conf_decay)
 
             pbar.update(1*batch_size)
           
 
-def boost_frame(safe_frame, base_frame, dt, decay=1):
+def boost_frame(safe_frame, base_frame, dt, power=1, decay=1):
     safe_boxes = safe_frame[:, :4]
     boxes = xywh2xyxy(base_frame[:, :4])  # center_x, center_y, width, height) to (x1, y1, x2, y2)
     ious = box_iou(boxes, safe_boxes)
     score = torch.matmul(ious, safe_frame[:, 4])
     # score = iou(safe_box, base_box) * confidence(safe_box)
-    base_frame[:, 4] *= 1 + (score)*math.exp(-decay*dt*dt)
+    base_frame[:, 4] *= 1 + power*(score)*math.exp(-decay*dt*dt)
     return base_frame
 
 def do_tracking(all_preds, image_meter_width, image_meter_height, gp=None, max_age=MAX_AGE, iou_thres=IOU_THRES, min_hits=MIN_HITS, min_length=MIN_LENGTH, verbose=True): 

scripts/track_detection.py

@@ -35,6 +35,8 @@ def main(args, config={}, verbose=True):
     if "iou_threshold" not in config: config['iou_threshold'] = 0.01
     if "min_hits" not in config: config['min_hits'] = 11
     if "use_associative" not in config: config['use_associative'] = False
+    if "boost_power" not in config: config['boost_power'] = 1
+    if "boost_decay" not in config: config['boost_decay'] = 1
 
     print(config)
 
@@ -102,7 +104,7 @@ def track(in_loc_dir, out_loc_dir, metadata_path, seq, config, verbose):
 
     if config['use_associative']:
 
-        do_confidence_boost(inference, outputs, verbose=verbose)
+        do_confidence_boost(inference, outputs, conf_power=config['boost_power'], conf_decay=config['boost_decay'], verbose=verbose)
 
         outputs = do_suppression(inference, conf_thres=config['conf_threshold'], iou_thres=config['nms_iou'], verbose=verbose)
 

scripts/track_eval.py

@@ -25,6 +25,8 @@ def main(args):
         'max_age': int(args.max_age),
         'iou_threshold': float(args.iou_threshold),
         'min_hits': int(args.min_hits),
+        'boost_power': int(args.boost_power),
+        'boost_decay': int(args.boost_decay),
         'use_associative': args.use_associative
     }
 
@@ -42,6 +44,8 @@ def argument_parser():
     parser.add_argument("--max_age", default=20, help="Config object. Required.")
     parser.add_argument("--iou_threshold", default=0.01, help="Config object. Required.")
     parser.add_argument("--min_hits", default=11, help="Config object. Required.")
+    parser.add_argument("--boost_power", default=1, help="Config object. Required.")
+    parser.add_argument("--boost_decay", default=1, help="Config object. Required.")
     parser.add_argument("--use_associative", action='store_true', help="Config object. Required.")
     return parser