68 lines
1.8 KiB
Python
68 lines
1.8 KiB
Python
#!/usr/bin/env python3
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import os
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import logging
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import tempfile
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import requests
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from cnn_classifier import Classifier
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def run_everything(parameters: dict):
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tag = parameters['tag']
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sample_file_handle, sample_file_path = tempfile.mkstemp(prefix=f"{tag}_", suffix=".wav")
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model_file_handle, model_file_path = tempfile.mkstemp(suffix=".json")
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weights_file_handle, weights_file_path = tempfile.mkstemp(suffix=".h5")
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try:
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logging.info(f"Downloading sample: {tag}")
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r = requests.get(f"http://storage-service/object/{tag}")
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with open(sample_file_handle, 'wb') as f:
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f.write(r.content)
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logging.debug(f"Downloaded sample to {sample_file_path}")
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r = requests.get(f"http://model-service/model/cnn/$default")
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r.raise_for_status()
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with open(model_file_handle, 'wb') as f:
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f.write(r.content)
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r = requests.get(f"http://model-service/model/cnn/$default?weights")
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r.raise_for_status()
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with open(weights_file_handle, 'wb') as f:
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f.write(r.content)
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# magic happens here
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classifier = Classifier(model_file_path, weights_file_path)
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results = classifier.predict(sample_file_path)
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finally: # bruuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuh
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try:
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os.remove(model_file_path)
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except FileNotFoundError:
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pass
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try:
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os.remove(weights_file_path)
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except FileNotFoundError:
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pass
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try:
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os.remove(sample_file_path)
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except FileNotFoundError:
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pass
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response = {
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"tag": tag,
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"probability": 1.0 if results[0] == 'sturnus' else 0.0,
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"model": ...
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}
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logging.info(f"Classification done!")
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logging.debug(f"Results: {response}")
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return response
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