=
69 lines
1.3 KiB
Plaintext
69 lines
1.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Load model"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import tensorflow as tf\n",
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"tf.enable_eager_execution()\n",
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"from model import DepthEstimate\n",
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"\n",
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"model = DepthEstimate()\n",
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"checkpoint_path = \"training_1/cp.ckpt\"\n",
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"model.load_weights(checkpoint_path)\n",
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"\n",
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"print('Model weights loaded.')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Load and evalute on Eigen's test data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from evaluate import load_test_data, evaluate\n",
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"\n",
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"rgb, depth, crop = load_test_data()\n",
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"evaluate(model, rgb, depth, crop)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python [conda env:tf_gpu] *",
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"language": "python",
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"name": "conda-env-tf_gpu-py"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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