From c86c91c96157a74eb5c2686916bf5fcc918ce8af Mon Sep 17 00:00:00 2001
From: soumajm <sm176357@outlook.com>
Date: Wed, 25 May 2022 17:12:49 +0800
Subject: [PATCH] Remove redundant variables in Yolox

Signed-off-by: Vittorio Cozzolino <vittorio.cozzolino@huawei.com>
---
 .../detection/yolox/exps/yolox_s_mix_det.py   | 14 +------
 .../detection/yolox/yolox/exp/base_exp.py     |  4 +-
 .../detection/yolox/yolox/exp/yolox_base.py   | 39 +------------------
 3 files changed, 3 insertions(+), 54 deletions(-)

diff --git a/examples/multiedgetracking/detection/yolox/exps/yolox_s_mix_det.py b/examples/multiedgetracking/detection/yolox/exps/yolox_s_mix_det.py
index 7b8d386e..33e6e4ec 100644
--- a/examples/multiedgetracking/detection/yolox/exps/yolox_s_mix_det.py
+++ b/examples/multiedgetracking/detection/yolox/exps/yolox_s_mix_det.py
@@ -10,16 +10,4 @@ class Exp(MyExp):
         self.depth = 0.33
         self.width = 0.50
         self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0]
-        self.train_ann = "train.json"
-        self.val_ann = "train.json"
-        self.input_size = (608, 1088)
-        self.test_size = (608, 1088)
-        self.random_size = (12, 26)
-        self.max_epoch = 80
-        self.print_interval = 20
-        self.eval_interval = 5
-        self.test_conf = 0.001
-        self.nmsthre = 0.7
-        self.no_aug_epochs = 10
-        self.basic_lr_per_img = 0.001 / 64.0
-        self.warmup_epochs = 1
+
diff --git a/examples/multiedgetracking/detection/yolox/yolox/exp/base_exp.py b/examples/multiedgetracking/detection/yolox/yolox/exp/base_exp.py
index 6fd79bc5..7e42a892 100644
--- a/examples/multiedgetracking/detection/yolox/yolox/exp/base_exp.py
+++ b/examples/multiedgetracking/detection/yolox/yolox/exp/base_exp.py
@@ -16,9 +16,6 @@ class BaseExp(metaclass=ABCMeta):
 
     def __init__(self):
         self.seed = None
-        self.output_dir = "./YOLOX_outputs"
-        self.print_interval = 100
-        self.eval_interval = 10
 
     @abstractmethod
     def get_model(self) -> Module:
@@ -32,3 +29,4 @@ class BaseExp(metaclass=ABCMeta):
             if not k.startswith("_")
         ]
         return None
+
diff --git a/examples/multiedgetracking/detection/yolox/yolox/exp/yolox_base.py b/examples/multiedgetracking/detection/yolox/yolox/exp/yolox_base.py
index 02dec64e..fcb09884 100644
--- a/examples/multiedgetracking/detection/yolox/yolox/exp/yolox_base.py
+++ b/examples/multiedgetracking/detection/yolox/yolox/exp/yolox_base.py
@@ -20,43 +20,6 @@ class Exp(BaseExp):
         self.depth = 1.00
         self.width = 1.00
 
-        # ---------------- dataloader config ---------------- #
-        # set worker to 4 for shorter dataloader init time
-        self.data_num_workers = 4
-        self.input_size = (640, 640)
-        self.random_size = (14, 26)
-        self.train_ann = "instances_train2017.json"
-        self.val_ann = "instances_val2017.json"
-
-        # --------------- transform config ----------------- #
-        self.degrees = 10.0
-        self.translate = 0.1
-        self.scale = (0.1, 2)
-        self.mscale = (0.8, 1.6)
-        self.shear = 2.0
-        self.perspective = 0.0
-        self.enable_mixup = True
-
-        # --------------  training config --------------------- #
-        self.warmup_epochs = 5
-        self.max_epoch = 300
-        self.warmup_lr = 0
-        self.basic_lr_per_img = 0.01 / 64.0
-        self.scheduler = "yoloxwarmcos"
-        self.no_aug_epochs = 15
-        self.min_lr_ratio = 0.05
-        self.ema = True
-
-        self.weight_decay = 5e-4
-        self.momentum = 0.9
-        self.print_interval = 10
-        self.eval_interval = 10
-        self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0]
-
-        # -----------------  testing config ------------------ #
-        self.test_size = (640, 640)
-        self.test_conf = 0.001
-        self.nmsthre = 0.65
 
     def get_model(self):
         from yolox.yolox.models import YOLOPAFPN, YOLOX, YOLOXHead
@@ -75,4 +38,4 @@ class Exp(BaseExp):
 
         self.model.apply(init_yolo)
         self.model.head.initialize_biases(1e-2)
-        return self.model
\ No newline at end of file
+        return self.model