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Tiny Yolo / Tiny Yolo VOC conv1 layer blob issues
The tiny yolo
and tiny yolo voc
caffemodel
files don't seem to agree with the prototxt
files.
I get an error that the source layer blob size mismatches for conv1_bn
. (see below)
Trying to troubleshoot didn't completely fix the problem (Changed the bias_term
value to true
in conv1_scale, and ran into another similar error for layer conv1
(bottom))
If I'm on the right track in debugging this, do you have updated matching prototxt files to match the caffemodel files?
Thanks, Chris
Error#1 (conv1_bn) text:
I0220 01:28:09.700489 16 net.cpp:222] conv1 does not need backward computation.
I0220 01:28:09.700492 16 net.cpp:222] data does not need backward computation.
I0220 01:28:09.700496 16 net.cpp:264] This network produces output result
I0220 01:28:09.700521 16 net.cpp:284] Network initialization done.
F0220 01:28:09.787974 16 net.cpp:797] Check failed: target_blobs.size() == source_layer.blobs_size() (5 vs. 3) Incompatible number of blobs for layer conv1_bn
*** Check failure stack trace: ***
Aborted (core dumped)
Error#2 (conv1) text:
I0220 01:30:58.295387 39 net.cpp:222] pool1 does not need backward computation.
I0220 01:30:58.295390 39 net.cpp:222] relu1 does not need backward computation.
I0220 01:30:58.295393 39 net.cpp:222] conv1_scale does not need backward computation.
I0220 01:30:58.295397 39 net.cpp:222] conv1_bn does not need backward computation.
I0220 01:30:58.295400 39 net.cpp:222] conv1 does not need backward computation.
I0220 01:30:58.295403 39 net.cpp:222] data does not need backward computation.
I0220 01:30:58.295408 39 net.cpp:264] This network produces output result
I0220 01:30:58.295436 39 net.cpp:284] Network initialization done.
F0220 01:30:58.384305 39 net.cpp:797] Check failed: target_blobs.size() == source_layer.blobs_size() (2 vs. 1) Incompatible number of blobs for layer conv1
*** Check failure stack trace: ***
Aborted (core dumped)
@chord, first of all thanks for debugging the YOLO model.
Can you give me some information on your system, e.g.:
- OS (Linux, Windows)
- Python version and type (e.g. if you are using Anaconda)
- Caffe commit hash and if you are using the CPU / GPU version
I checked the models with the last Windows release of Caffe (GPU) under Python 3.5 (Anaconda) and it's working correctly. I'll also check on my Linux laptop to verify that the layer parameters didn't change recently.
I'm also assuming that you are using the converted .caffemodel
files from YOLO; the links are at the end of the Installation section.