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Runtime error
| import tensorflow as tf | |
| import numpy as np | |
| import gradio as gr | |
| import matplotlib.pyplot as plt | |
| from huggingface_hub import from_pretrained_keras | |
| import os | |
| import sys | |
| print('Loading model...') | |
| model = from_pretrained_keras("mostafapasha/ribs-segmentation-model", compile=False) | |
| print('Successfully loaded model...') | |
| examples = ['examples/VinDr_RibCXR_train_008.png', 'examples/VinDr_RibCXR_train_013.png'] | |
| def infer(img, threshold): | |
| if np.ndim(img) != 2: | |
| img = img[:, :, 1] | |
| img = img.reshape(1, img.shape[0], img.shape[1], 1) | |
| logits = model(img, training=False) | |
| prob = tf.sigmoid(logits) | |
| pred = tf.cast(prob > threshold, dtype=tf.float32) | |
| pred = np.array(pred.numpy())[0,:,:,0] | |
| return pred | |
| gr_input = [ | |
| gr.inputs.Image(label="Image", type="numpy", shape=(512, 512)) | |
| ,gr.inputs.Slider(minimum=0, maximum=1, step=0.05, default=0.5, label="Segmentation Threshold") | |
| ] | |
| gr_output = [ | |
| gr.outputs.Image(type="pil",label="Segmentation Mask"), | |
| # gr.outputs.Image(type="pil",label="Filtered Image"), | |
| ] | |
| iface = gr.Interface(fn=infer, | |
| title = 'ribs segmentation model', | |
| description = 'Keras implementation of ResUNET++ for xray ribs segmentation', | |
| inputs=gr_input, | |
| outputs=gr_output, examples=examples, flagging_dir="flagged").launch(cache_examples=True) | |