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πŸ“’ logo-identifier-model

This model has been trained on a dataset called "LogoIdentifier" for multi-class classification of logos from 57 renowned brands and companies. These brands encompass a wide spectrum of industries and recognition, ranging from global giants like Coca-Cola, Coleman, Google, IBM, Nike, Pepsi, and many others. Each brand is thoughtfully organized into its designated subfolder, housing a comprehensive set of logo images for precise and accurate classification. Whether you're identifying iconic logos or exploring the branding diversity of these 57 famous names, this model is your go-to solution for logo recognition and classification.

πŸ§ͺ Dataset Content

  • The dataset includes logos from various brands and companies.
  • The dataset is organized into subfolders, each corresponding to a specific brand or company.
  • It contains a wide range of brand logos, including Acer, Acura, Adidas, Samsung, Lenovo, McDonald's, Java, and many more.
  • Each brand or company in the dataset is associated with a numerical value, likely representing the number of images available for that brand.

The model has been trained to recognize and classify logos into their respective brand categories based on the images provided in the dataset.

Company Quantity of images
Acer 67
Acura 74
Addidas 90
Ades 36
Adio 63
Cadillac 69
CalvinKlein 65
Canon 59
Cocacola 40
CocaColaZero 91
Coleman 57
Converse 60
CornFlakes 62
DominossPizza 99
Excel 88
Gillette 86
GMC 75
Google 93
HardRockCafe 93
HBO 103
Heineken 84
HewlettPackard 81
Hp 87
Huawei 84
Hyundai 84
IBM 84
Java 62
KFC 84
Kia 76
Kingston 79
Lenovo 82
LG 95
Lipton 94
Mattel 77
McDonalds 98
MercedesBenz 94
Motorola 86
Nestle 94
Nickelodeon 74
Nike 50
Pennzoil 82
Pepsi 93
Peugeot 60
Porsche 71
Samsung 96
SchneiderElectric 42
Shell 58

To use this model for brand logo identification, you can make use of the Hugging Face Transformers library and load the model using its model ID (90194144191). You can then input an image of a brand logo, and the model should be able to predict the brand it belongs to based on its training.

πŸ€— Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 90194144191
  • CO2 Emissions (in grams): 0.0608

πŸ“ Validation Metrics

  • Loss: 0.300
  • Accuracy: 0.924
  • Macro F1: 0.924
  • Micro F1: 0.924
  • Weighted F1: 0.922
  • Macro Precision: 0.930
  • Micro Precision: 0.924
  • Weighted Precision: 0.928
  • Macro Recall: 0.924
  • Micro Recall: 0.924
  • Weighted Recall: 0.924
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