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Hey, I created facenet_engine.plan file using the facenet.onnx file. When I ran the code for inference, it didn't gave any correct recognition results. I compared the embeddings (same image) generated from facenet.h5 and facenet_engine.plan file, it turns out that they both are COMPLETELY DIFFERENT. What could possibly be the reason for this strange result?
Also, I got error "AssertionError: Bottleneck_BatchNorm/batchnorm_1/add_1:0 is not in graph" while converting from facenet.pb to facenet.onnx. So, I used the command "python -m tf2onnx.convert --input path-to-facenet.pb --inputs input:0[1,160,160,3] --inputs-as-nchw input_1:0 --outputs Bottleneck/BatchNorm/batchnorm/add_1:0 --output path-to-save-facenet.onnx" instead. Later one worked without causing any error.
Please help me to get the right embeddings!
Thank you!
The text was updated successfully, but these errors were encountered:
Hey, I created facenet_engine.plan file using the facenet.onnx file. When I ran the code for inference, it didn't gave any correct recognition results. I compared the embeddings (same image) generated from facenet.h5 and facenet_engine.plan file, it turns out that they both are COMPLETELY DIFFERENT. What could possibly be the reason for this strange result?
Also, I got error "AssertionError: Bottleneck_BatchNorm/batchnorm_1/add_1:0 is not in graph" while converting from facenet.pb to facenet.onnx. So, I used the command "python -m tf2onnx.convert --input path-to-facenet.pb --inputs input:0[1,160,160,3] --inputs-as-nchw input_1:0 --outputs Bottleneck/BatchNorm/batchnorm/add_1:0 --output path-to-save-facenet.onnx" instead. Later one worked without causing any error.
Please help me to get the right embeddings!
Thank you!
Hi, did you follow all the instructions mentioned in the develop branch?
Hey, I created facenet_engine.plan file using the facenet.onnx file. When I ran the code for inference, it didn't gave any correct recognition results. I compared the embeddings (same image) generated from facenet.h5 and facenet_engine.plan file, it turns out that they both are COMPLETELY DIFFERENT. What could possibly be the reason for this strange result?
Also, I got error "AssertionError: Bottleneck_BatchNorm/batchnorm_1/add_1:0 is not in graph" while converting from facenet.pb to facenet.onnx. So, I used the command "python -m tf2onnx.convert --input path-to-facenet.pb --inputs input:0[1,160,160,3] --inputs-as-nchw input_1:0 --outputs Bottleneck/BatchNorm/batchnorm/add_1:0 --output path-to-save-facenet.onnx" instead. Later one worked without causing any error.
Please help me to get the right embeddings!
Thank you!
The text was updated successfully, but these errors were encountered: