<jupyter_start><jupyter_text>Load model<jupyter_code>import tensorflow as tf
tf.enable_eager_execution()
from model import DepthEstimate

model = DepthEstimate()
checkpoint_path = "training_1/cp.ckpt"
model.load_weights(checkpoint_path)

print('Model weights loaded.')<jupyter_output><empty_output><jupyter_text>Load and evalute on Eigen's test data<jupyter_code>from evaluate import load_test_data, evaluate

rgb, depth, crop = load_test_data()
evaluate(model, rgb, depth, crop)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.0962671905697446, 'fraction_numerical': 0.0019646365422396855, 'mean_word_length': 9.851063829787234, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '70184', 'license': 'MIT', 'n_tokens_mistral': 183, 'n_tokens_neox': 175, 'n_words': 36, 'path': 'Tensorflow/Evaluate.ipynb', 'repo_name': 'anuragal/DepthModel', 'size': '509'}