sanrio-classifier-resnet18

Sanrio Classifier — ResNet18

ResNet18 fine-tuned to classify 29 Sanrio characters from images. Exported to ONNX for lightweight CPU inference.

Model Description

• Architecture: ResNet18 (Transfer Learning)
• Input: 224x224 RGB images
• Output: 29 Sanrio character classes with confidence scores
• Format: ONNX (FP32 and INT8 quantized)
• Size: 43 MB (FP32) / 11 MB (INT8)

Classes

badtz_maru, chococat, cinnamon, cinnamoroll, gudetama, hangyodon, hello_kitty, kerokerokeroppi, kuromi, little_twin_stars, melody, my_sweet_piano, pochacco, pompompurin, purin, rilakkuma, shin_chan, sumikko_gurashi, tuxedo_sam

Usage (Python)

`python import onnxruntime as ort import numpy as np from PIL import Image

sess = ort.InferenceSession('tl_sanrio_v5_int8.onnx') img = Image.open('character.jpg').resize((224, 224)) input_tensor = np.array(img).transpose(2,0,1).astype(np.float32) / 255.0 input_tensor = np.expand_dims(input_tensor, axis=0)

outputs = sess.run(['softmax_1'], {'input.1': input_tensor}) pred_class = outputs[0].argmax() confidence = outputs[0].max() `

Demo

Try it live: https://huggingface.co/spaces/MorritaConP1to/sanrio-classifier

Training

• Framework: PyTorch with Transfer Learning
• Optimizer: SGD with CosineAnnealing LR
• Dataset: ~6,160 images across 29 classes
• Hardware: NVIDIA RTX 4060