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Merge pull request aws#70 from awslabs/image_classification_notebooks
Changed hosting image and fixed missing cells
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‎introduction_to_amazon_algorithms/imageclassification_caltech/Image-classification-fulltraining.ipynb

Lines changed: 38 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -57,7 +57,6 @@
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"role = re.sub(r'^(.+)sts::(\\d+):assumed-role/(.+?)/.*$', r'\\1iam::\\2:role/\\3', assumed_role)\n",
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"\n",
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"bucket='<<bucket-name>>' # customize to your bucket\n",
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"\n",
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"containers = {'us-west-2': '433757028032.dkr.ecr.us-west-2.amazonaws.com/image-classification:latest',\n",
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" 'us-east-1': '811284229777.dkr.ecr.us-east-1.amazonaws.com/image-classification:latest',\n",
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" 'us-east-2': '825641698319.dkr.ecr.us-east-2.amazonaws.com/image-classification:latest',\n",
@@ -340,8 +339,13 @@
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"model_data = info['ModelArtifacts']['S3ModelArtifacts']\n",
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"print(model_data)\n",
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"\n",
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"containers = {'us-west-2': '433757028032.dkr.ecr.us-west-2.amazonaws.com/image-classification:latest',\n",
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" 'us-east-1': '811284229777.dkr.ecr.us-east-1.amazonaws.com/image-classification:latest',\n",
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" 'us-east-2': '825641698319.dkr.ecr.us-east-2.amazonaws.com/image-classification:latest',\n",
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" 'eu-west-1': '685385470294.dkr.ecr.us-west-1.amazonaws.com/image-classification:latest'}\n",
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"hosting_image = containers[boto3.Session().region_name]\n",
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"primary_container = {\n",
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" 'Image': \"032969728358.dkr.ecr.us-west-2.amazonaws.com/image-classification:latest\",\n",
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" 'Image': hosting_image,\n",
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" 'ModelDataUrl': model_data,\n",
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"}\n",
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"\n",
@@ -363,6 +367,36 @@
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"In addition, the endpoint configuration describes the instance type required for model deployment, and at launch will describe the autoscaling configuration."
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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 time import gmtime, strftime\n",
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"\n",
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"timestamp = time.strftime('-%Y-%m-%d-%H-%M-%S', time.gmtime())\n",
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"endpoint_config_name = job_name_prefix + '-epc-' + timestamp\n",
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"endpoint_config_response = sage.create_endpoint_config(\n",
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" EndpointConfigName = endpoint_config_name,\n",
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" ProductionVariants=[{\n",
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" 'InstanceType':'ml.p2.xlarge',\n",
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" 'InitialInstanceCount':3,\n",
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" 'ModelName':model_name,\n",
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" 'VariantName':'AllTraffic'}])\n",
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"\n",
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"print('Endpoint configuration name: {}'.format(endpoint_config_name))\n",
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"print('Endpoint configuration arn: {}'.format(endpoint_config_response['EndpointConfigArn']))"
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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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"### Create Endpoint\n",
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"Lastly, the customer creates the endpoint that serves up the model, through specifying the name and configuration defined above. The end result is an endpoint that can be validated and incorporated into production applications. This takes 9-11 minutes to complete."
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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,
@@ -460,7 +494,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"!wget -O /tmp/test.jpg https://static.pexels.com/photos/47319/phone-dial-old-arrangement-47319.jpeg\n",
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"!wget -O /tmp/test.jpg http://www.vision.caltech.edu/Image_Datasets/Caltech256/images/008.bathtub/008_0007.jpg\n",
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"file_name = '/tmp/test.jpg'\n",
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"# test image\n",
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"from IPython.display import Image\n",
@@ -480,7 +514,7 @@
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" payload = f.read()\n",
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" payload = bytearray(payload)\n",
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"response = runtime.invoke_endpoint(EndpointName=endpoint_name, \n",
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" ContentType='image/jpeg', \n",
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" ContentType='application/x-image', \n",
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" Body=payload)\n",
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"result = response['Body'].read()\n",
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"# result will be in json format and convert it to ndarray\n",

‎introduction_to_amazon_algorithms/imageclassification_caltech/Image-classification-transfer-learning.ipynb

Lines changed: 51 additions & 19 deletions
Original file line numberDiff line numberDiff line change
@@ -45,7 +45,9 @@
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"%%time\n",
@@ -79,7 +81,9 @@
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import os\n",
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"isConfigCell": true
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},
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"outputs": [],
@@ -182,7 +187,9 @@
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"%%time\n",
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# create the Amazon SageMaker training job\n",
@@ -290,7 +299,9 @@
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"training_info = sagemaker.describe_training_job(TrainingJobName=job_name)\n",
@@ -341,7 +352,9 @@
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"%%time\n",
@@ -355,9 +368,13 @@
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"info = sage.describe_training_job(TrainingJobName=job_name)\n",
356369
"model_data = info['ModelArtifacts']['S3ModelArtifacts']\n",
357370
"print(model_data)\n",
358-
"\n",
371+
"containers = {'us-west-2': '433757028032.dkr.ecr.us-west-2.amazonaws.com/image-classification:latest',\n",
372+
" 'us-east-1': '811284229777.dkr.ecr.us-east-1.amazonaws.com/image-classification:latest',\n",
373+
" 'us-east-2': '825641698319.dkr.ecr.us-east-2.amazonaws.com/image-classification:latest',\n",
374+
" 'eu-west-1': '685385470294.dkr.ecr.us-west-1.amazonaws.com/image-classification:latest'}\n",
375+
"hosting_image = containers[boto3.Session().region_name]\n",
359376
"primary_container = {\n",
360-
" 'Image': \"032969728358.dkr.ecr.us-west-2.amazonaws.com/image-classification:latest\",\n",
377+
" 'Image': hosting_image,\n",
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" 'ModelDataUrl': model_data,\n",
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"}\n",
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"\n",
@@ -382,7 +399,9 @@
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"from time import gmtime, strftime\n",
@@ -412,7 +431,9 @@
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"%%time\n",
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# get the status of the endpoint\n",
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import boto3\n",
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"!wget -O /tmp/test.jpg https://static.pexels.com/photos/47319/phone-dial-old-arrangement-47319.jpeg\n",
536+
"!wget -O /tmp/test.jpg http://www.vision.caltech.edu/Image_Datasets/Caltech256/images/008.bathtub/008_0007.jpg\n",
510537
"file_name = '/tmp/test.jpg'\n",
511538
"# test image\n",
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"from IPython.display import Image\n",
@@ -516,17 +543,18 @@
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import json\n",
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"import numpy as np\n",
524-
"endpoint_name='ImageClassificationITE2017-11-25-03-55-18'\n",
525553
"with open(file_name, 'rb') as f:\n",
526554
" payload = f.read()\n",
527555
" payload = bytearray(payload)\n",
528556
"response = runtime.invoke_endpoint(EndpointName=endpoint_name, \n",
529-
" ContentType='application/image', \n",
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" ContentType='application/x-image', \n",
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" Body=payload)\n",
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"result = response['Body'].read()\n",
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"# result will be in json format and convert it to ndarray\n",
@@ -550,7 +578,9 @@
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"#sage.delete_endpoint(EndpointName=endpoint_name)\n",
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}

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