luisarizmendi
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Update README.md
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README.md
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metrics:
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- type: precision
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name: Precision
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value: 0.
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- type: recall
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name: Recall
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value: 0.
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- type: mAP50
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name: mAP50
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value: 0.
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- type: mAP50-95
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name: mAP50-95
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value: 0.
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---
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# Model for detecting Hardhats and Hats
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<div align="center">
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<img width="640" alt="luisarizmendi/
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</div>
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## Model binary
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You can [download the model from here](https://github.com/luisarizmendi/ai-apps/raw/refs/heads/main/models/luisarizmendi/object-
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## Labels
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```
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## Model metrics
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<div align="center">
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<img width="640" alt="luisarizmendi/
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</div>
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[https://universe.roboflow.com/luisarizmendi/hardhat-or-hat](https://universe.roboflow.com/luisarizmendi/hardhat-or-hat)
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## Model training
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You can [review the Jupyter notebook here](https://huggingface.co/luisarizmendi/hardhat-or-hat/blob/main/train.ipynb)
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### Hyperparameters
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```
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## Usage
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### Usage with Huggingface spaces
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</div>
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### Usage with Python script
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Install the following PIP requirements
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torch
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```
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Then [run the python code below](https://
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```
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import gradio as gr
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import cv2
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import torch
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DEFAULT_MODEL_URL = "https://github.com/luisarizmendi/ai-apps/raw/refs/heads/main/models/luisarizmendi/object-
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def detect_objects_in_files(model_input, files):
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"""
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if __name__ == "__main__":
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interface.launch()
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metrics:
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- type: precision
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name: Precision
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value: 0.844
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- type: recall
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name: Recall
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value: 0.847
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- type: mAP50
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name: mAP50
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value: 0.893
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- type: mAP50-95
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name: mAP50-95
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value: 0.546
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---
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# Model for detecting Hardhats and Hats
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<div align="center">
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<img width="640" alt="luisarizmendi/hardhat-or-hat" src="example.png">
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</div>
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## Model binary
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You can [download the model from here](https://github.com/luisarizmendi/ai-apps/raw/refs/heads/main/models/luisarizmendi/object-detection-hardhat-or-hat/object-detection-hardhat-or-hat-m.pt)
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## Labels
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```
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## Base Model
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Ultralytics/YOLO11m
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## Model metrics
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```
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YOLO11m summary (fused): 303 layers, 20,032,345 parameters, 0 gradients, 67.7 GFLOPs
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Class Images Instances Box(P R mAP50 mAP50-95)
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all 1992 15306 0.844 0.847 0.893 0.546
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hat 244 287 0.869 0.811 0.876 0.578
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helmet 1202 3942 0.916 0.892 0.942 0.61
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no_helmet 741 11077 0.746 0.838 0.861 0.45
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```
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<div align="center">
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<img width="640" alt="luisarizmendi/hardhat-or-hat" src="confusion_matrix_normalized.png"> <img width="640" alt="luisarizmendi/hardhat-or-hat" src="results.png">
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</div>
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[https://universe.roboflow.com/luisarizmendi/hardhat-or-hat](https://universe.roboflow.com/luisarizmendi/hardhat-or-hat)
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## Model training
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You can [review the Jupyter notebook here](https://github.com/luisarizmendi/ai-apps/blob/main/dev/hardhat-or-hat/train.ipynb)
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### Hyperparameters
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```
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## Model Usage
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### Usage with Huggingface spaces
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</div>
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### Usage with Python script
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Install the following PIP requirements
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torch
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```
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Then [run the python code below ](https://github.com/luisarizmendi/ai-apps/raw/refs/heads/main/models/luisarizmendi/object-detector-hardhat-or-hat/run_model.py) and open `http://localhost:7860` in a browser to upload and scan the images.
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```
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import gradio as gr
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import cv2
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import torch
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DEFAULT_MODEL_URL = "https://github.com/luisarizmendi/ai-apps/raw/refs/heads/main/models/luisarizmendi/object-detection-hardhat-or-hat/object-detection-hardhat-or-hat-m.pt"
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def detect_objects_in_files(model_input, files):
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"""
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if __name__ == "__main__":
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interface.launch()
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```
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