README.md

metadata

library_name: tflite
pipeline_tag: image-classification
tags:
  - image-classification
  - tflite
  - tensorflow
  - gender-classification
base_model: rizvandwiki/gender-classification-2

Gender classification (TensorFlow / TFLite)

TensorFlow and TFLite conversion of rizvandwiki/gender-classification-2 (ViT). Please check the original model card for license and training details.

Files

• gender_model.tflite : mobile model (float16)
• tf_model.h5 : TensorFlow (Keras) weights
• labels.txt : 0 = female, 1 = male

Input / preprocessing

• Shape: [1, 3, 224, 224] (channels first, RGB)
• Normalize: (pixel / 255 - 0.5) / 0.5
• Detect and crop the face before running the model.
• Output: 2 logits -> apply softmax.

Note: converted with SELECT_TF_OPS, so on Android add org.tensorflow:tensorflow-lite-select-tf-ops.

Python example

import numpy as np, tensorflow as tf
from huggingface_hub import hf_hub_download

path = hf_hub_download("SynthAIzer/gender-classification-tflite", "gender_model.tflite")
interp = tf.lite.Interpreter(model_path=path)
interp.allocate_tensors()