As a volunteer at 'Le Refuge,' a local animal protection association, I embarked on a mission to develop a machine learning tool that could aid in the classification of dog breeds from their vast image database. The project was inspired by my own experience finding my beloved pet, Snooky, through this association. To give back, I aimed to streamline their data management process by implementing an advanced breed classification algorithm.
from transformers import pipeline
# Specify the model you want to use
model_name = "amaye15/ViT-Standford-Dogs"# Example: Vision Transformer# Load the image classification pipeline with the specified model
image_classifier = pipeline("image-classification", model=model_name)
# Path or URL to your image
image_path_or_url = "path_or_url_to_your_image"# Get predictions
predictions = image_classifier(image_path_or_url)
# Define the number of top predictions you want to see (top k)
top_k = 5# Print the top k predictionsfor prediction in predictions[:top_k]:
print(f"Class: {prediction['label']}, Confidence: {prediction['score']:.2f}")
Runs of amaye15 ViT-Standford-Dogs on huggingface.co
44
Total runs
5
24-hour runs
31
3-day runs
30
7-day runs
22
30-day runs
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ViT-Standford-Dogs is an open source model from GitHub that offers a free installation service, and any user can find ViT-Standford-Dogs on GitHub to install. At the same time, huggingface.co provides the effect of ViT-Standford-Dogs install, users can directly use ViT-Standford-Dogs installed effect in huggingface.co for debugging and trial. It also supports api for free installation.