cnn-classification-service/cnn_classification_service/magic_doer.py
marcsello 4003aa73ac
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Updated for new model service api
2020-10-02 03:59:09 +02:00

84 lines
2.3 KiB
Python

#!/usr/bin/env python3
import os
import logging
import tempfile
import requests
from urllib.parse import urljoin
from cnn_classifier import Classifier
def run_everything(parameters: dict):
tag = parameters['tag']
sample_file_handle, sample_file_path = tempfile.mkstemp(prefix=f"{tag}_", suffix=".wav")
model_file_handle, model_file_path = tempfile.mkstemp(suffix=".json")
weights_file_handle, weights_file_path = tempfile.mkstemp(suffix=".h5")
try:
# Download Sample
logging.info(f"Downloading sample: {tag}")
r = requests.get(f"http://storage-service/object/{tag}")
with open(sample_file_handle, 'wb') as f:
f.write(r.content)
logging.debug(f"Downloaded sample to {sample_file_path}")
# Download model
model_root_url = "http://model-service/model/cnn/$default"
logging.debug("Fetching model info...")
r = requests.get(model_root_url)
r.raise_for_status()
model_details = r.json()
logging.debug("Fetching model file...")
r = requests.get(urljoin(model_root_url, model_details['files']['model'])) # Fun fact: this would support external urls
r.raise_for_status()
with open(model_file_handle, 'wb') as f:
f.write(r.content)
logging.debug("Fetching weights file...")
r = requests.get(urljoin(model_root_url, model_details['files']['weights']))
r.raise_for_status()
with open(weights_file_handle, 'wb') as f:
f.write(r.content)
# magic happens here
classifier = Classifier(model_file_path, weights_file_path)
results = classifier.predict(sample_file_path)
finally: # bruuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuh
try:
os.remove(model_file_path)
except FileNotFoundError:
pass
try:
os.remove(weights_file_path)
except FileNotFoundError:
pass
try:
os.remove(sample_file_path)
except FileNotFoundError:
pass
response = {
"tag": tag,
"probability": 1.0 if results[0] == model_details['target_class_name'] else 0.0,
"model": model_details['id']
}
logging.info(f"Classification done!")
logging.debug(f"Results: {response}")
return response