Alaric Dobson

Hi Ludwig, I am successfully training using TensorFlow 1.8.0 on the standard SSD MobileNet V1 model config file, and exporting graphs using the object_detection script "export_inference_graph.py". I'm working in continuous...

I've made myself a kit for working with Lucid on the many families of frozen graphs produced by my experiments (with SSD Mobilenet PPN). https://github.com/brentcroft/lucid-spritemaps  I'm experimenting with varying...

I had 128, and tried up to 2048, with the declared error varying: ``` (0) Invalid argument: Incompatible shapes: [1,16,490,490] vs. [1,16,419,363] [[node import/FeatureExtractor/MobilenetV3/expanded_conv/squeeze_excite/mul (defined at D:\Miniconda3\envs\tf-gpu2\lib\site-packages\lucid-0.3.9-py3.7.egg\lucid\modelzoo\vision_base.py:200) ]] [[Mean/_27]] (1)...

I downloaded the trained MobileNet V3 graph file "Small dm=0.75 (float)" from here (https://github.com/tensorflow/models/tree/master/research/slim/nets/mobilenet), extracted the files into my "D:/temp", and ran the following code: ``` import tensorflow as tf...

In "modelzoo/slim_models", the various models each provide a hard-coded list of layers. E.g. MobilenetV2.py ``` MobilenetV2_10_slim.layers = _layers_from_list_of_dicts(MobilenetV2_10_slim, [ ... {'tags': ['conv'], 'name': 'MobilenetV2/expanded_conv_15/add', 'depth': 160}, {'tags': ['dense'], 'name': 'MobilenetV2/Predictions/Softmax',...