├── .gitignore
├── README.md
├── demo.pb
└── dump.py


/.gitignore:
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1 | __pycache__
2 | *.egg-info
3 | 


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/README.md:
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 1 | # tensorboard-dumper
 2 | requires: `pip install tensorboard`
 3 | 
 4 | This tool dumps images in tensorboard.
 5 | 
 6 | tested on python3
 7 | 
 8 | `python dump.py` dumps the images in the file `events.out.tfevents.` which is generated by tensorboard-pytorch's demo.py
 9 | 
10 | You can find the `events.out.tfevents...` file in the `runs` folder in tensorboard-pytorch after running `python demo.py`.
11 | 


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/demo.pb:
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https://raw.githubusercontent.com/lanpa/tensorboard-dumper/57e505553eef0a27cd2e400793bc6397176a5c55/demo.pb


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/dump.py:
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 1 | import struct
 2 | import tensorboard.compat.proto.event_pb2 as event_pb2
 3 | import io
 4 | import argparse
 5 | 
 6 | 
 7 | def read(data):
 8 |     header = struct.unpack('Q', data[:8])
 9 | 
10 |     # crc_hdr = struct.unpack('I', data[:4])
11 |     
12 |     event_str = data[12:12+int(header[0])] # 8+4
13 |     data = data[12+int(header[0])+4:]
14 |     return data, event_str
15 | 
16 |     # crc_ev = struct.unpack('>I', data[:4])
17 |     
18 | 
19 | 
20 | def save_img(encoded, step, save_gif):
21 |     from PIL import Image
22 |     img = Image.open(io.BytesIO(encoded))
23 |     if save_gif:
24 |         images.append(img)
25 |     else:
26 |         img.save('img_{}.png'.format(step), format='png')
27 | 
28 | 
29 | parser = argparse.ArgumentParser(description='tensorboard-dumper')
30 | parser.add_argument('--gif', default=False, action='store_true', help='save result as gif')
31 | parser.add_argument('--input', default='demo.pb', help='saved tensorboard file to read from')
32 | parser.add_argument('--output', default='output.gif', help='output filename for gif export')
33 | parser.add_argument('--maxframe', default=100, help='limit the number of frames')
34 | parser.add_argument('--duration', default=100, help='show time for each frame (ms)')
35 | 
36 | args = parser.parse_args()
37 | 
38 | 
39 | try:
40 |     with open(args.input, 'rb') as f:
41 |         data = f.read()
42 | except FileNotFoundError:
43 |     print('input file not found')
44 |     exit()
45 | 
46 | images = []
47 | 
48 | while data and args.maxframe>0:
49 |     args.maxframe = args.maxframe-1
50 |     data, event_str = read(data)
51 |     event = event_pb2.Event()
52 | 
53 |     event.ParseFromString(event_str)
54 |     if event.HasField('summary'):
55 |         for value in event.summary.value:
56 |             if value.HasField('simple_value'):
57 |                 print(value.simple_value, value.tag, event.step)
58 |             if value.HasField('image'):
59 |                 img = value.image
60 |                 save_img(img.encoded_image_string, event.step, save_gif=args.gif)
61 |                 print('img saved.')
62 | 
63 | if args.gif:
64 |     from PIL import Image
65 |     im = images[0]
66 |     im.save(args.output, save_all=True, append_images=images, duration=100, loop=0) # forever
67 |  
68 | 


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