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@@ -37,28 +37,28 @@ model-index:
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  metrics:
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  - type: precision
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  name: Precision
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- value: 0.9078
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  - type: recall
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  name: Recall
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- value: 0.9064
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  - type: mAP50
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  name: mAP50
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- value: 0.9589
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  - type: mAP50-95
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  name: mAP50-95
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- value: 0.6088
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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/safety-equipment" src="https://huggingface.co/luisarizmendi/hardhat-or-hat/resolve/main/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-detector-hardhat-or-hat/object-detector-hardhat-or-hat.pt)
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  ## Labels
@@ -70,11 +70,24 @@ You can [download the model from here](https://github.com/luisarizmendi/ai-apps/
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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/safety-equipment" src="https://huggingface.co/luisarizmendi/hardhat-or-hat/resolve/main/confusion_matrix_normalized.png"> <img width="640" alt="luisarizmendi/safety-equipment" src="https://huggingface.co/luisarizmendi/hardhat-or-hat/resolve/main/results.png">
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  </div>
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@@ -83,12 +96,9 @@ You can [download the model from here](https://github.com/luisarizmendi/ai-apps/
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  [https://universe.roboflow.com/luisarizmendi/hardhat-or-hat](https://universe.roboflow.com/luisarizmendi/hardhat-or-hat)
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-
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  ## Model training
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- ### Notebook
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-
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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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@@ -125,8 +135,7 @@ mixup=0.0, # Image mixup
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  ```
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- ## Usage
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-
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  ### Usage with Huggingface spaces
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@@ -139,6 +148,7 @@ Remember to check that the Model URL is pointing to the model that you want to t
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  </div>
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  ### Usage with Python script
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  Install the following PIP requirements
@@ -151,7 +161,8 @@ opencv-python
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  torch
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  ```
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- Then [run the python code below](https://huggingface.co/luisarizmendi/hardhat-or-hat/blob/main/run_model.py) and then 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
@@ -161,7 +172,7 @@ import os
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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-detector-hardhat-or-hat/object-detector-hardhat-or-hat.pt"
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  def detect_objects_in_files(model_input, files):
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  """
@@ -213,4 +224,9 @@ interface = gr.Interface(
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  if __name__ == "__main__":
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  interface.launch()
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- ```
 
 
 
 
 
 
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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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+
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+ Ultralytics/YOLO11m
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+
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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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+
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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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+
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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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  ```
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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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+ ```
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+
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+