- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
I have installed the latest version of ncsdk2 which provides support for tf ssd as per release notes(2.10) but when I am trying to load the graph file it say dynamic input mode is not supported. The input node name given is image_tensor. Appreciate any support on this issue .. thank you
Link Copied
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
I also encountered the same error.
After run mvNCCompile -h
, I found there's a --tf-ssd-config
option. So I used the following command to compile the model:
mvNCCompile frozen_inference_graph.pb -s 12 -in image_tensor -on detection_boxes --tf-ssd-config pipeline.config
Now the error message is:
Traceback (most recent call last):
File "/usr/local/bin/mvNCCompile", line 208, in <module>
args.old_parser, args.cpp, args)
File "/usr/local/bin/mvNCCompile", line 186, in create_graph
load_ret = load_network(args, parser, myriad_config)
File "/usr/local/bin/ncsdk/Controllers/Scheduler.py", line 70, in load_network
p.load_ssd_config(arguments.tf_ssd_config)
File "/usr/local/bin/ncsdk/Controllers/Parsers/TensorFlow.py", line 237, in load_ssd_config
text_format.Parse(config_pb.read(), self.ssd_config)
File "/usr/lib/python3.5/site-packages/google/protobuf/text_format.py", line 499, in Parse
descriptor_pool=descriptor_pool)
File "/usr/lib/python3.5/site-packages/google/protobuf/text_format.py", line 563, in ParseLines
return parser.ParseLines(lines, message)
File "/usr/lib/python3.5/site-packages/google/protobuf/text_format.py", line 613, in ParseLines
self._ParseOrMerge(lines, message)
File "/usr/lib/python3.5/site-packages/google/protobuf/text_format.py", line 638, in _ParseOrMerge
self._MergeField(tokenizer, message)
File "/usr/lib/python3.5/site-packages/google/protobuf/text_format.py", line 730, in _MergeField
(message_descriptor.full_name, name))
google.protobuf.text_format.ParseError: 1:1 : Message type "TFSSDConfig" has no field named "model".
And I have no clue about this…
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
I tried to inspect the error message of Message type "TFSSDConfig" has no field named "model".
, but still have no solution to it.
The "model" name was from the beginning of the file pipeline.config
for the --tf-ssd-config
option. The starting lines of my pipeline.config
is:
model {
ssd {
num_classes: 90
image_resizer {
fixed_shape_resizer {
height: 300
width: 300
}
}
If anyone know how to solve it, or know any example of compiling Tensoflow Mobilenet SSD into NCS graph, please give some help. Thank you.
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
I also have same problem.
OS : ubuntu 16.0.4
NCSDK : 2.10.01.01
Command line : mvNCCompile frozen_inference_graph.pb -s 12 --tf-ssd-config pipeline.config
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Any updates? Has the same issue here.
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hi @eric_huang @Edjoz @hiankun @sreerag_ibtl
We just posted a thread about the new --tf-ssd-config
option for the NCSDK v2.10.
Take a look: NCSDK 2.10 OPTION: --tf-ssd-config
Regards,
Jesus
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Thank you @Jesus_at_Intel. I have some doubts. I couldn't find the parameters 'background_label_id' and 'box_params' in the original pipeline.config. The model was trained using the object detection api.
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hi @sreerag_ibtl
The background_label_id
is technically a class but it’s used when nothing is detected and will consider it as part of the background. Some networks utilize this background class and other don’t. I believe they are inherently based on how the model is trained.
The box_params
values represent the variance of the bounding boxes, the 0.1 value is used for the center of the bounding box and the 0.2 value is used for the width and height settings.
Hope this helps!
Regards,
Jesus
![](/skins/images/B7BA37F9CE4B52FF7CAE1FB0388839C8/responsive_peak/images/icon_anonymous_message.png)
- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page