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harshai-a/
HarsAI

Name: HarsAI
Availability: InStock

pytorch

vit

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harshai-a / HarsAI

like 0 Image Classification PyTorch

ciplab/real-and-fake-face-detection vit vision transformer fake-image-detection Eval Results

License: apache-2.0 Model card Files Community 1 HarsAi / README.md

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tags:

vision
image-classification
vit
transformer
fake-image-detection license: apache-2.0 datasets:
ciplab/real-and-fake-face-detection model-index:
name: HarsAi results:
- task: name: Image Classification type: image-classification dataset: name: Real and Fake Face Detection Dataset type: ciplab/real-and-fake-face-detection metrics:
  - name: Accuracy type: accuracy value: 99.12
  - name: Precision type: precision value: 98.95
  - name: Recall type: recall value: 99.00

HarsAi - Enhanced Fake Image Detection Model

SahAi is a fine-tuned Vision Transformer (ViT) model designed for fake image localization in social media.

🚀 Model Description

Base Model: ViT-B/16
Input Size: 224x224
Output Classes: Real (0), Fake (1)

🔥 How to Use

python

from transformers import ViTForImageClassification, AutoFeatureExtractor
from PIL import Image
import torch
model = ViTForImageClassification.from_pretrained("harshai-a/HarsAI")
feature_extractor = AutoFeatureExtractor.from_pretrained("google/vit-base-patch16-224-in21k")
image = Image.open("test_image.jpg").convert("RGB")
inputs = feature_extractor(images=image, return_tensors="pt")
with torch.no_grad():
    outputs = model(**inputs)
    prediction = outputs.logits.argmax(-1).item()
print("Real" if prediction == 0 else "Fake")