Unify batched and non-batched versions
42892de
Luigi
commited on
Commit History
Show FPS on demo video
15801f5
Support Inference over batch with TensorRT Engine Model
0cdc9a7
Use dynamic batch size by default
09ccc6e
Add script used to convert ONNX to fp32/fp16/int8/mixed engine
92676db
Use ONNXruntime instead of ONNX.checker.check_model to detect ONNX model
57a8c6b
Resize in keeping aspect ratio in visualization
35b2a45
fix postprocess_batch method in RTMO_GPU_Batch class
6008f96
Add model format (ONNX/Engine) & input size detection (based on file header, not on filename) for RTMO
58a44cf
Add support TensorRT engine support for RTMO
bbf20b6
Re-quantize models in FP16 in keep positional encoding in FP32 to avoid bad accuracy
f9a6075
verified
Improve Debug Message Layout in Validate Funciton
e8f08e3
Add appropriate pre- to input image and postprocessing to validate function
6dfe441
Validate only on pose result, add visual check
b58a63b
Add comparison between joint coordinated from original and converted models
ab55aa6
Add 'rtol', 'atol' arguments to control tolerance in model validation
684ebde
Fix Input Type Error raised in infer()
18eb8e3
Add utility to convert ONNX model in FP32/16 mixed precision
9f60e86
Load ./libmmdeploy_tensorrt_ops.so for TensorRT EP if available
1c5dc58
Remove fix_batch_dimension_all.sh
01042ef
Remove models with fixed batch size as dynamic batch is generally supported
ae1686f
Apply constant folding
d474b05
Reperform shape inference on all models
e7b68a5
Bugfix: correct batch dimension fixation then regenerate ONNX models
e4e03fd
Luigi
commited on