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79 lines
2.5 KiB
79 lines
2.5 KiB
#!/usr/bin/env python |
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import os |
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import sys |
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import time |
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import urllib |
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import hashlib |
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import argparse |
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import json |
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def reporthook(count, block_size, total_size): |
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""" |
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From http://blog.moleculea.com/2012/10/04/urlretrieve-progres-indicator/ |
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""" |
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global start_time |
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global prev_duration |
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if count == 0: |
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start_time = time.time() |
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prev_duration = -1 |
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return |
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duration = max(1, time.time() - start_time) |
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if int(duration) == int(prev_duration): |
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return |
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progress_size = int(count * block_size) |
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speed = int(progress_size / (1024 * duration)) |
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percent = int(count * block_size * 100 / total_size) |
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sys.stdout.write("\r...%d%%, %d MB, %d KB/s, %d seconds passed" % |
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(percent, progress_size / (1024 * 1024), speed, duration)) |
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sys.stdout.flush() |
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prev_duration = duration |
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# Function for checking SHA1. |
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def model_checks_out(filename, sha1): |
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with open(filename, 'r') as f: |
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return hashlib.sha1(f.read()).hexdigest() == sha1 |
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def model_download(filename, url, sha1): |
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# Check if model exists. |
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if os.path.exists(filename) and model_checks_out(filename, sha1): |
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print("Model {} already exists.".format(filename)) |
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return |
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# Download and verify model. |
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urllib.urlretrieve(url, filename, reporthook) |
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print model_checks_out(filename, sha1) |
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if not model_checks_out(filename, sha1): |
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print("ERROR: model {} did not download correctly!".format(url)) |
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sys.exit(1) |
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if __name__ == '__main__': |
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parser = argparse.ArgumentParser(description="Downloading trained model binaries.") |
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parser.add_argument("download_list") |
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args = parser.parse_args() |
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test_dir = os.environ.get("OPENCV_TEST_DATA_PATH") |
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if not test_dir: |
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print "ERROR: OPENCV_TEST_DATA_PATH environment not specified" |
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sys.exit(1) |
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try: |
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with open(args.download_list, 'r') as f: |
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models_to_download = json.load(f) |
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except: |
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print "ERROR: Can't pasrse {}".format(args.download_list) |
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sys.exit(1) |
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for model_name in models_to_download: |
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model = models_to_download[model_name] |
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dst_dir = os.path.join(test_dir, os.path.dirname(model['file'])) |
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dst_file = os.path.join(test_dir, model['file']) |
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if not os.path.exists(dst_dir): |
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print "ERROR: Can't find module testdata path '{}'".format(dst_dir) |
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sys.exit(1) |
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print "Downloading model '{}' to {} from {} ...".format(model_name, dst_file, model['url']) |
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model_download(dst_file, model['url'], model['sha1']) |