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[MOD | FIX] -> object_detection.ipynb #5

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Jan 12, 2022
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[MOD | FIX] -> object_detection.ipynb #5

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124 changes: 63 additions & 61 deletions object_detection.ipynb
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Original file line number Diff line number Diff line change
@@ -1,19 +1,4 @@
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Copy of Copy of object-detection.ipynb",
"provenance": [],
"collapsed_sections": [],
"toc_visible": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
Expand All @@ -26,25 +11,27 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "GmloKE6Qx8Lu"
},
"outputs": [],
"source": [
"credentials = {\n",
" \"bucket\": \"BUCKET\",\n",
" \"access_key_id\": \"ACCESS_KEY_ID\",\n",
" \"secret_access_key\": \"SECRET_ACCESS_KEY\",\n",
" \"endpoint_url\": \"ENDPOINT_URL\"\n",
"}"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "hVPzEKoLuEHy"
},
"outputs": [],
"source": [
"NUM_TRAIN_STEPS = 500\n",
"MODEL_TYPE = 'ssd_mobilenet_v1_quantized_300x300_coco14_sync_2018_07_18'\n",
Expand All @@ -62,9 +49,7 @@
"LABEL_MAP_PATH = os.path.join(DATA_PATH, 'label_map.pbtxt')\n",
"TRAIN_RECORD_PATH = os.path.join(DATA_PATH, 'train.record')\n",
"VAL_RECORD_PATH = os.path.join(DATA_PATH, 'val.record')"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand All @@ -89,9 +74,11 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "o33_jgwGm3NV"
},
"outputs": [],
"source": [
"%tensorflow_version 1.x\n",
"import os\n",
Expand All @@ -114,9 +101,7 @@
"\n",
"pwd = os.getcwd()\n",
"os.environ['PYTHONPATH'] += f':{pwd}:{pwd}/slim'"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand All @@ -130,14 +115,14 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "iM8sOHwL64Rp"
},
"outputs": [],
"source": [
"!python object_detection/builders/model_builder_tf1_test.py"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand All @@ -151,15 +136,15 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "jydTH9gYQ3y7"
},
"outputs": [],
"source": [
"import cloud_annotations as ca\n",
"ca.mount(CLOUD_ANNOTATIONS_MOUNT, credentials)"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand Down Expand Up @@ -191,9 +176,11 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "nJsKCG3UdDsn"
},
"outputs": [],
"source": [
"import os\n",
"import json\n",
Expand All @@ -213,9 +200,7 @@
" f.write(\"\\tname: '{}'\\n\".format(label))\n",
" f.write('\\tid: {}\\n'.format(idx + 1)) # indexes must start at 1\n",
" f.write('}\\n')"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand Down Expand Up @@ -247,17 +232,21 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "cAkOvP-gZR1x"
},
"outputs": [],
"source": [
"import os\n",
"import io\n",
"import json\n",
"import random\n",
"\n",
"import PIL.Image\n",
"import tensorflow as tf\n",
"import PIL.Image\n",
"from PIL import JpegImagePlugin\n",
"JpegImagePlugin._getmp = lambda x: None\n",
"\n",
"from object_detection.utils import dataset_util\n",
"from object_detection.utils import label_map_util\n",
Expand Down Expand Up @@ -328,8 +317,8 @@
" if tf_example:\n",
" # Write the TFExample to the TFRecord.\n",
" writer.write(tf_example.SerializeToString())\n",
" except ValueError:\n",
" print('Invalid example, ignoring.')\n",
" except ValueError as e:\n",
" print(e)\n",
" pass\n",
" except IOError:\n",
" print(\"Can't read example, ignoring.\")\n",
Expand All @@ -349,9 +338,7 @@
"\n",
" create_tf_record(train_examples, annotations, label_map, CLOUD_ANNOTATIONS_MOUNT, TRAIN_RECORD_PATH)\n",
" create_tf_record(val_examples, annotations, label_map, CLOUD_ANNOTATIONS_MOUNT, VAL_RECORD_PATH)"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand All @@ -375,9 +362,11 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "oHD1Jm0v7jfz"
},
"outputs": [],
"source": [
"import os\n",
"import tarfile\n",
Expand All @@ -401,9 +390,7 @@
" tar.extract(member, path=CHECKPOINT_PATH)\n",
"\n",
" os.remove(tmp)"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand All @@ -417,9 +404,11 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "C8CVExv6HsJS"
},
"outputs": [],
"source": [
"import re\n",
"\n",
Expand Down Expand Up @@ -447,9 +436,7 @@
"configs = config_util.merge_external_params_with_configs(configs, kwargs_dict=override_dict)\n",
"pipeline_config = config_util.create_pipeline_proto_from_configs(configs)\n",
"config_util.save_pipeline_config(pipeline_config, DATA_PATH)"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand All @@ -467,19 +454,19 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Wv5h2bwBVO0V"
},
"outputs": [],
"source": [
"!rm -rf $OUTPUT_PATH\n",
"!python -m object_detection.model_main \\\n",
" --pipeline_config_path=$DATA_PATH/pipeline.config \\\n",
" --model_dir=$OUTPUT_PATH \\\n",
" --num_train_steps=$NUM_TRAIN_STEPS \\\n",
" --num_eval_steps=100"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand All @@ -495,9 +482,11 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "BZgP_FZUoE0d"
},
"outputs": [],
"source": [
"import os\n",
"import re\n",
Expand All @@ -513,9 +502,7 @@
" --pipeline_config_path=$DATA_PATH/pipeline.config \\\n",
" --trained_checkpoint_prefix=$TRAINED_CHECKPOINT_PREFIX \\\n",
" --output_directory=$EXPORTED_PATH"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand All @@ -531,9 +518,11 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "HWHvlnyjmCIN"
},
"outputs": [],
"source": [
"from IPython.display import display, Javascript, Image\n",
"from google.colab.output import eval_js\n",
Expand Down Expand Up @@ -642,9 +631,7 @@
" line_thickness=8)\n",
" plt.figure(figsize=(12, 8))\n",
" plt.imshow(image_np)"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand All @@ -660,9 +647,11 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "A-f5lfcnp01e"
},
"outputs": [],
"source": [
"!tensorflowjs_converter \\\n",
" --input_format=tf_frozen_model \\\n",
Expand All @@ -684,9 +673,7 @@
" json.dump(label_array, f)\n",
"\n",
"!cd /content/model_web && zip -r /content/model_web.zip *"
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand All @@ -702,15 +689,15 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "FL_miSj2r1yt"
},
"outputs": [],
"source": [
"from google.colab import files\n",
"files.download('/content/model_web.zip') "
],
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
Expand All @@ -722,5 +709,20 @@
"Use the `model_web` folder generated here, with this [project](https://github.com/cloud-annotations/object-detection-react) to create a real-time webcam object detection app."
]
}
]
],
"metadata": {
"accelerator": "GPU",
"colab": {
"collapsed_sections": [],
"name": "Copy of Copy of object-detection.ipynb",
"provenance": [],
"toc_visible": true
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
}
},
"nbformat": 4,
"nbformat_minor": 0
}