30 lines
1.3 KiB
Python
Executable File
30 lines
1.3 KiB
Python
Executable File
import dask.dataframe as dd
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from azure.cognitiveservices.vision.customvision.training import CustomVisionTrainingClient
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from azure.cognitiveservices.vision.customvision.prediction import CustomVisionPredictionClient
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from azure.cognitiveservices.vision.customvision.training.models import ImageFileCreateBatch, ImageFileCreateEntry, Region
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from msrest.authentication import ApiKeyCredentials
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import os, time, uuid
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ENDPOINT = "https://trashvision.cognitiveservices.azure.com/"
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training_key = "611e786a785648e38f346f18e7f7e7ed"
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prediction_key = "611e786a785648e38f346f18e7f7e7ed"
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project_id = "a67f7d7b-c980-49bd-b57d-0bd1367b29d0"
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credentials = ApiKeyCredentials(in_headers={"Training-key": training_key})
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trainer = CustomVisionTrainingClient(ENDPOINT, credentials)
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prediction_credentials = ApiKeyCredentials(in_headers={"Prediction-key": prediction_key})
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predictor = CustomVisionPredictionClient(ENDPOINT, prediction_credentials)
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print ("Training...")
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iteration = trainer.train_project(project_id)
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while (iteration.status != "Completed"):
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iteration = trainer.get_iteration(project_id, iteration.id)
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print ("Training status: " + iteration.status)
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time.sleep(1)
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# The iteration is now trained. Publish it to the project endpoint
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trainer.publish_iteration(project_id, iteration.id, "HaxNet1", predictor)
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print ("Done!")
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