refactor!: move yolov8custommodel to top level of project

model/detect/config.yaml

@@ -0,0 +1,18 @@
+# config.yaml
+optimizer: AdamW
+epochs: 50
+batch_size: 16
+imgsz: 640
+learning_rate: 0.002
+momentum: 0.937
+weight_decay: 0.0005
+augmentation:
+  flip_lr: 0.5
+  mosaic: 1.0
+  mixup: 0.0
+  hsv_h: 0.015
+  hsv_s: 0.7
+  hsv_v: 0.4
+  degrees: 5
+  translate: 0.1
+  scale: 0.5

model/detect/data.yaml

@@ -0,0 +1,10 @@
+path: data
+
+# data.yaml
+train: images/train # Path to training dataset
+val: images/val # Path to validation dataset
+
+nc: 1 # Number of classes (update as per your classes)
+names:
+  ["car"]
+  # Update with class names

model/detect/main.py

@@ -0,0 +1,54 @@
+from torchvision import transforms
+from ultralytics import YOLO
+
+# Configuration for data augmentation
+transform = transforms.Compose(
+    [
+        transforms.RandomHorizontalFlip(p=0.5),
+        transforms.ColorJitter(brightness=0.4, contrast=0.4, saturation=0.4, hue=0.1),
+        transforms.RandomRotation(degrees=5),
+        transforms.RandomResizedCrop((640, 640), scale=(0.8, 1.2)),
+    ]
+)
+
+
+def train_model():
+    # Initialize YOLO model with pretrained weights
+    model = YOLO(
+        "yolov8n.yaml"
+    )  # You can use yolov8n.pt if you want to use the pretrained model
+
+    # Update training settings in model
+    model.train(
+        data="data.yaml",
+        epochs=100,  # Increase epochs to 100 for better training
+        batch=8,  # Use batch size of 8 to avoid NMS time limit issues
+        imgsz=512,  # Reduce image size to 512x512 for faster training
+        optimizer="AdamW",  # AdamW optimizer for improved convergence
+        lr0=0.0015,  # Fine-tune the learning rate for smoother learning
+        lrf=0.005,  # Adjust learning rate final value for slower decay
+        momentum=0.9,  # Momentum for better optimization
+        weight_decay=0.0001,  # Lower weight decay to prevent over-regularization
+        augment=True,  # Enable augmentation for better generalization
+        mosaic=1.0,  # Mosaic augmentation to improve robustness
+        mixup=0.2,  # Introduce MixUp data augmentation
+        hsv_h=0.015,  # Adjust HSV for more varied color augmentation
+        hsv_s=0.7,
+        hsv_v=0.4,
+        degrees=10,  # Increase the rotation degrees to allow more flexibility
+        translate=0.2,  # Allow higher translation augmentation
+        scale=0.6,  # Slightly higher scaling range for augmentation
+        flipud=0.1,  # Flip images upside down 10% of the time
+        fliplr=0.5,  # Left-right flip augmentationn m
+        max_det=1000,  # Allow up to 1000 detections to handle crowded scenes
+        patience=50,  # Early stopping patience to avoid overfitting
+        project="runs/detect",
+        name="train_augmented_tuned",  # Updated name to reflect fine-tuning
+        workers=4,  # Keep a lower number of workers for better resource management
+        amp=True,  # Re-enable mixed precision to speed up training
+        verbose=True,  # Display progress logs during training
+    )
+
+
+if __name__ == "__main__":
+    train_model()

model/detect/obj.data

@@ -0,0 +1,4 @@
+classes = 1
+train = data/train.txt
+names = data/obj.names
+backup = backup/

model/detect/obj.names

@@ -0,0 +1 @@
+car

model/detect/obj_train_data/2024-10-08_18-26-21_1.25999999687243_103.823611110166.txt

@@ -0,0 +1,8 @@
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model/detect/obj_train_data/2024-10-08_18-26-21_1.26027777363278_103.823888890049.txt

@@ -0,0 +1,16 @@
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model/detect/obj_train_data/2024-10-08_18-26-21_1.27066408655104_103.856977943394.txt

@@ -0,0 +1,10 @@
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model/detect/obj_train_data/2024-10-08_18-26-21_1.27237_103.8324.txt

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model/detect/obj_train_data/2024-10-08_18-26-21_1.27414394350065_103.851316802547.txt

@@ -0,0 +1 @@
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model/detect/obj_train_data/2024-10-08_18-26-21_1.27877_103.82375.txt

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model/detect/obj_train_data/2024-10-08_18-26-21_1.28036584335876_103.830451146503.txt

@@ -0,0 +1,10 @@
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model/detect/obj_train_data/2024-10-08_18-26-21_1.28569398886979_103.837524510188.txt

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model/detect/obj_train_data/2024-10-08_18-26-21_1.2871_103.79633.txt

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model/detect/obj_train_data/2024-10-08_18-26-21_1.29158484_103.8615987.txt

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model/detect/obj_train_data/2024-10-08_18-26-21_1.29409891409364_103.876056196568.txt

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model/detect/obj_train_data/2024-10-08_18-26-21_1.29565733262976_103.885283049309.txt

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