Added model.pt
Browse files- README.md +60 -0
- events.out.tfevents.1699156391.66327ba9d198.4870.0 +3 -0
- model.pt +3 -0
- training_artifacts/args.yaml +100 -0
- training_artifacts/results.png +0 -0
README.md
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---
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license: mit
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---
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---
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license: mit
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library: ultralytics
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tags:
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- object-detection
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- pytorch
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- ultralytics
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- roboflow-universe
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- human-detection
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- yolov8
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---
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# Human Detection using Thermal Camera
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## Use Case
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## Evaluation Metrics
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__Weights & Biases__: [Run Details](https://wandb.ai/2wb2ndur/Human-Detection-Thermal-Camera/runs/5j95496q/overview?workspace=user-2wb2ndur)
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### Training Graphs
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![Training Graphs](./training_artifacts/results.png)
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## Training Code
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- Dataset Link: [Roboflow Universe](https://universe.roboflow.com/smart2/persondection-61bc2)
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```python
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from ultralytics import YOLO
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import torch
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# load model
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model = YOLO("yolov8n.pt")
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# hyper parameters
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hyperparams = {
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"batch": 32,
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"epochs": 30,
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"imgsz": [640, 480],
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"optimizer": "AdamW",
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"cos_lr": True,
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"lr0": 3e-5,
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"warmup_epochs": 10
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}
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# start training
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model.train(
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device = 'cuda' if torch.cuda.is_available() else 'cpu',
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data = "data.yaml",
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**hyperparams
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)
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```
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- Click here for: [Training Arguments](./training_artifacts/args.yaml)
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## Libraries
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```yaml
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python: 3.10.13
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ultralytics: 8.0.206
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torch: "2.1.0+cu118"
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roboflow: 1.1.9
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```
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events.out.tfevents.1699156391.66327ba9d198.4870.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:4b0211290e4600ad85a77be909aa628de21b6612245d33b5c85cc861f52cb0db
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size 764723
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model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:63181e6c024a8a218020932b516bfb9547130e03e07c8d4671cb2973df038bef
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size 6234201
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training_artifacts/args.yaml
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task: detect
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mode: train
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model: yolov8n.pt
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data: data.yaml
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epochs: 30
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patience: 50
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batch: 32
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imgsz:
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- 640
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- 480
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save: true
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save_period: -1
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cache: false
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device: 0
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workers: 8
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project: Human-Detection-Thermal-Camera
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name: radiant-armadillo-1
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exist_ok: false
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pretrained: true
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optimizer: AdamW
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verbose: true
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seed: 0
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deterministic: true
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single_cls: false
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rect: false
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cos_lr: true
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close_mosaic: 10
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resume: false
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amp: true
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fraction: 1.0
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profile: false
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freeze: null
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overlap_mask: true
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mask_ratio: 4
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dropout: 0.0
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val: true
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split: val
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save_json: false
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save_hybrid: false
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conf: null
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iou: 0.7
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max_det: 300
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half: false
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dnn: false
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plots: true
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source: null
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show: false
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save_txt: false
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save_conf: false
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save_crop: false
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show_labels: true
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show_conf: true
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vid_stride: 1
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stream_buffer: false
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line_width: null
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visualize: false
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augment: false
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agnostic_nms: false
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classes: null
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retina_masks: false
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boxes: true
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format: torchscript
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keras: false
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optimize: false
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int8: false
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dynamic: false
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simplify: false
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opset: null
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workspace: 4
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nms: false
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lr0: 3.0e-05
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lrf: 0.01
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momentum: 0.937
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weight_decay: 0.0005
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warmup_epochs: 10
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warmup_momentum: 0.8
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warmup_bias_lr: 0.1
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box: 7.5
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cls: 0.5
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dfl: 1.5
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pose: 12.0
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kobj: 1.0
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label_smoothing: 0.0
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nbs: 64
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hsv_h: 0.015
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hsv_s: 0.7
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hsv_v: 0.4
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degrees: 0.0
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translate: 0.1
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scale: 0.5
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shear: 0.0
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perspective: 0.0
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flipud: 0.0
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fliplr: 0.5
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mosaic: 1.0
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mixup: 0.0
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copy_paste: 0.0
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cfg: null
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tracker: botsort.yaml
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save_dir: Human-Detection-Thermal-Camera/radiant-armadillo-1
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training_artifacts/results.png
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