
# CSGO Weapon Classification

This is a CSGO Weapon Classifier Model that has been trained by [Kaludi](https://huggingface.co/Kaludi) to recognize **11** different types of Counter-Strike: Global Offensive (CSGO) Weapons, which include **AK-47,AWP,Famas,Galil-AR,Glock,M4A1,M4A4,P-90,SG-553,UMP,USP**. The model is capable of accurately classifying the weapon name present in an image. With its deep understanding of the characteristics of each weapon in the game, the model is a valuable tool for players and fans of CSGO.

### Gradio

Tis model supports a [Gradio](https://github.com/gradio-app/gradio) Web UI to run the csgo-weapon-classification model:
[![Open In HF Spaces](https://camo.githubusercontent.com/00380c35e60d6b04be65d3d94a58332be5cc93779f630bcdfc18ab9a3a7d3388/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f25463025394625413425393725323048756767696e67253230466163652d5370616365732d626c7565)](https://huggingface.co/spaces/Kaludi/CSGO-Weapon-Classification_App)


## Validation Metrics

- Loss: 0.282
- Accuracy: 0.945
- Macro F1: 0.946
- Micro F1: 0.945
- Weighted F1: 0.946
- Macro Precision: 0.948
- Micro Precision: 0.945
- Weighted Precision: 0.948
- Macro Recall: 0.945
- Micro Recall: 0.945
- Weighted Recall: 0.945
{"tags": ["vision", "image-classification", "CSGO"], "datasets": ["Kaludi/data-csgo-weapon-classification"], "widget": [{"src": "https://media.moddb.com/images/downloads/1/219/218947/render.png", "example_title": "AK47"}, {"src": "https://lh6.googleusercontent.com/36GwQuG6pKBsW1HEFNLwC1cEUp4nzX8NgWh0G7ruR5YpGJwBm4DoUFsGwZmKN5AXNyTsFmgXvV07OFIEy-33lPPJJb9PZZndE_-xYqWaaWmDhoqaMoIJAF7xXh4-xO2mufoTsgdn", "example_title": "AWP"}, {"src": "https://community.akamai.steamstatic.com/economy/image/-9a81dlWLwJ2UUGcVs_nsVtzdOEdtWwKGZZLQHTxDZ7I56KU0Zwwo4NUX4oFJZEHLbXH5ApeO4YmlhxYQknCRvCo04DEVlxkKgpopuP1FAR17PDJZS5J-dC6h7-bzqfLP7LWnn9u5MRjjeyPpYrz2lfhqEZvMm_6JdOXelJrYVqDrlbsxe66hp-56JjKnXowvCgg42GdwUIaw99WQg/360fx360f", "example_title": "P90"}, {"src": "https://www.talkesport.com/wp-content/uploads/csgo-new-update.jpg", "example_title": "M4A1"}, {"src": "https://mir-s3-cdn-cf.behance.net/project_modules/fs/c6040519785195.562e039771066.png", "example_title": "USP"}], "co2_eq_emissions": {"emissions": 0.0421564161796381}}
transformers pytorch swin image-classification vision CSGO dataset:Kaludi/data-csgo-weapon-classification co2_eq_emissions autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #swin #image-classification #vision #CSGO #dataset-Kaludi/data-csgo-weapon-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 


# CSGO Weapon Classification

This is a CSGO Weapon Classifier Model that has been trained by Kaludi to recognize 11 different types of Counter-Strike: Global Offensive (CSGO) Weapons, which include AK-47,AWP,Famas,Galil-AR,Glock,M4A1,M4A4,P-90,SG-553,UMP,USP. The model is capable of accurately classifying the weapon name present in an image. With its deep understanding of the characteristics of each weapon in the game, the model is a valuable tool for players and fans of CSGO.

### Gradio

Tis model supports a Gradio Web UI to run the csgo-weapon-classification model:
![Open In HF Spaces](URL


## Validation Metrics

- Loss: 0.282
- Accuracy: 0.945
- Macro F1: 0.946
- Micro F1: 0.945
- Weighted F1: 0.946
- Macro Precision: 0.948
- Micro Precision: 0.945
- Weighted Precision: 0.948
- Macro Recall: 0.945
- Micro Recall: 0.945
- Weighted Recall: 0.945
# CSGO Weapon Classification

This is a CSGO Weapon Classifier Model that has been trained by Kaludi to recognize 11 different types of Counter-Strike: Global Offensive (CSGO) Weapons, which include AK-47,AWP,Famas,Galil-AR,Glock,M4A1,M4A4,P-90,SG-553,UMP,USP. The model is capable of accurately classifying the weapon name present in an image. With its deep understanding of the characteristics of each weapon in the game, the model is a valuable tool for players and fans of CSGO. ### Gradio

Tis model supports a Gradio Web UI to run the csgo-weapon-classification model:
![Open In HF Spaces](URL ## Validation Metrics

- Loss: 0.282
- Accuracy: 0.945
- Macro F1: 0.946
- Micro F1: 0.945
- Weighted F1: 0.946
- Macro Precision: 0.948
- Micro Precision: 0.945
- Weighted Precision: 0.948
- Macro Recall: 0.945
- Micro Recall: 0.945
- Weighted Recall: 0.945
TAGS
#transformers #pytorch #swin #image-classification #vision #CSGO #dataset-Kaludi/data-csgo-weapon-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # CSGO Weapon Classification

This is a CSGO Weapon Classifier Model that has been trained by Kaludi to recognize 11 different types of Counter-Strike: Global Offensive (CSGO) Weapons, which include AK-47,AWP,Famas,Galil-AR,Glock,M4A1,M4A4,P-90,SG-553,UMP,USP. The model is capable of accurately classifying the weapon name present in an image. With its deep understanding of the characteristics of each weapon in the game, the model is a valuable tool for players and fans of CSGO. ### Gradio

Tis model supports a Gradio Web UI to run the csgo-weapon-classification model:
![Open In HF Spaces](URL ## Validation Metrics

- Loss: 0.282
- Accuracy: 0.945
- Macro F1: 0.946
- Micro F1: 0.945
- Weighted F1: 0.946
- Macro Precision: 0.948
- Micro Precision: 0.945
- Weighted Precision: 0.948
- Macro Recall: 0.945
- Micro Recall: 0.945
- Weighted Recall: 0.945
TAGS
#transformers #pytorch #swin #image-classification #vision #CSGO #dataset-Kaludi/data-csgo-weapon-classification #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #region-us 
# CSGO Weapon Classification

This is a CSGO Weapon Classifier Model that has been trained by Kaludi to recognize 11 different types of Counter-Strike: Global Offensive (CSGO) Weapons, which include AK-47,AWP,Famas,Galil-AR,Glock,M4A1,M4A4,P-90,SG-553,UMP,USP. The model is capable of accurately classifying the weapon name present in an image. With its deep understanding of the characteristics of each weapon in the game, the model is a valuable tool for players and fans of CSGO.### Gradio

Tis model supports a Gradio Web UI to run the csgo-weapon-classification model:
![Open In HF Spaces](URL## Validation Metrics

- Loss: 0.282
- Accuracy: 0.945
- Macro F1: 0.946
- Micro F1: 0.945
- Weighted F1: 0.946
- Macro Precision: 0.948
- Micro Precision: 0.945
- Weighted Precision: 0.948
- Macro Recall: 0.945
- Micro Recall: 0.945
- Weighted Recall: 0.945