initial push

backend/project_54/54/exp.py

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+#!/usr/bin/env python3
+# -*- coding:utf-8 -*-
+# Copyright (c) Megvii, Inc. and its affiliates.
+
+import os
+
+from yolox.exp import Exp as MyExp
+
+
+class Exp(MyExp):
+    def __init__(self):
+        super(Exp, self).__init__()
+        self.data_dir = "/home/kitraining/To_Annotate/"
+        self.train_ann = "coco_project_54_train.json"
+        self.val_ann = "coco_project_54_valid.json"
+        self.test_ann = "coco_project_54_test.json"
+        self.num_classes = 3
+        self.pretrained_ckpt = r'/home/kitraining/Yolox/YOLOX-main/pretrained/YOLOX_s.pth'
+        self.depth = 0.33
+        self.width = 0.50
+        self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0]
+
+
+        # --------------  training config --------------------- #
+        
+        self.use_focal_loss = True         # Focal Loss for better class imbalance handling
+        self.focal_loss_alpha = 0.25
+        self.focal_loss_gamma = 1.5
+
+        self.warmup_epochs = 20           # More warmup    
+        self.max_epoch = 150              # More epochs for better convergence 
+        self.act = "silu"                 # Activation function
+        self.no_aug_epochs = 30           # No augmentation for last epochs to stabilize training
+
+        self.class_weights = [1.0, 1.0, 1.0] # Weights for each class to handle imbalance
+                
+        # Thresholds 
+        self.test_conf = 0.15            # Low to catch more the second class
+        self.nmsthre = 0.5               # IoU threshold for NMS         
+
+        # Data Augmentation intens to improve generalization
+        self.enable_mixup = True
+        self.mixup_prob = 0.7            # mixup
+        self.mosaic_prob = 0.8           # mosaico
+        self.degrees = 20.0              # Rotation
+        self.translate = 0.2             # Translation
+        self.scale = (0.5, 1.5)          # Scaling
+        self.shear = 5.0                 # Shear
+        self.flip_prob = 0.8
+        self.hsv_prob = 1.0
+        
+        # Learning rate 
+        self.basic_lr_per_img = 0.001 / 64.0  # Lower LR to avoid divergence
+        self.scheduler = "yoloxwarmcos" 
+        self.min_lr_ratio = 0.01
+        
+        # Loss weights
+        self.cls_loss_weight = 8.0       # More weight to the classification loss
+        self.obj_loss_weight = 1.0
+        self.reg_loss_weight = 1.0
+        
+        # Input size bigger for better detection of small objects like babys 
+        self.input_size = (832, 832)  
+        self.test_size = (832, 832)
+        
+        # Batch size
+        self.batch_size = 5              # Reduce if you have memory issues

backend/project_54/54/exp_infer.py

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+#!/usr/bin/env python3
+# -*- coding:utf-8 -*-
+# Copyright (c) Megvii, Inc. and its affiliates.
+
+import os
+
+from yolox.exp import Exp as MyExp
+
+
+class Exp(MyExp):
+    def __init__(self):
+        super(Exp, self).__init__()
+        self.data_dir = "/home/kitraining/To_Annotate/"
+        self.train_ann = "coco_project_54_train.json"
+        self.val_ann = "coco_project_54_valid.json"
+        self.test_ann = "coco_project_54_test.json"
+        self.num_classes = 2
+        self.pretrained_ckpt = r'/home/kitraining/Yolox/YOLOX-main/pretrained/YOLOX-s.pth'
+        self.depth = 1
+        self.width = 1
+        self.input_size = (640, 640)
+        self.mosaic_scale = (0.1, 2)
+        self.random_size = (10, 20)
+        self.test_size = (640, 640)
+        self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0]
+        self.enable_mixup = False