convert_script.txt

python convert_onnx.py

onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx
onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx
onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx
onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx


python nms_yolact_edge.py


docker run --gpus all -it --rm \
-v `pwd`:/home/user/workdir \
ghcr.io/pinto0309/tflite2tensorflow:latest


tflite2tensorflow \
--model_path nms_yolact_edge.tflite \
--flatc_path ../flatc \
--schema_path ../schema.fbs \
--output_pb \
--optimizing_for_openvino_and_myriad

tflite2tensorflow \
--model_path nms_yolact_edge.tflite \
--flatc_path ../flatc \
--schema_path ../schema.fbs \
--output_onnx \
--onnx_opset 11

mv saved_model/model_float32.onnx nms_yolact_edge.onnx




onnxsim nms_yolact_edge.onnx nms_yolact_edge.onnx
onnxsim nms_yolact_edge.onnx nms_yolact_edge.onnx
onnxsim nms_yolact_edge.onnx nms_yolact_edge.onnx
onnxsim nms_yolact_edge.onnx nms_yolact_edge.onnx


sor4onnx \
--input_onnx_file_path nms_yolact_edge.onnx \
--old_new "input_1" "nms_boxes" \
--output_onnx_file_path nms_yolact_edge.onnx \
--mode inputs

sor4onnx \
--input_onnx_file_path nms_yolact_edge.onnx \
--old_new "input_2" "nms_scores" \
--output_onnx_file_path nms_yolact_edge.onnx \
--mode inputs

sor4onnx \
--input_onnx_file_path nms_yolact_edge.onnx \
--old_new "input_3" "nms_classes" \
--output_onnx_file_path nms_yolact_edge.onnx \
--mode inputs

sor4onnx \
--input_onnx_file_path nms_yolact_edge.onnx \
--old_new "input_4" "nms_masks" \
--output_onnx_file_path nms_yolact_edge.onnx \
--mode inputs

sor4onnx \
--input_onnx_file_path nms_yolact_edge.onnx \
--old_new "input_5" "nms_proto" \
--output_onnx_file_path nms_yolact_edge.onnx \
--mode inputs



sor4onnx \
--input_onnx_file_path nms_yolact_edge.onnx \
--old_new "Identity_1" "proto_out" \
--output_onnx_file_path nms_yolact_edge.onnx \
--mode outputs

sor4onnx \
--input_onnx_file_path nms_yolact_edge.onnx \
--old_new "Identity" "x1y1x2y2_scores_classes_masks_4x1x1x32" \
--output_onnx_file_path nms_yolact_edge.onnx \
--mode outputs


snc4onnx \
--input_onnx_file_paths yolact_edge_mobilenetv2_54_800000.onnx nms_yolact_edge.onnx \
--op_prefixes_after_merging main post \
--srcop_destop boxes nms_boxes scores nms_scores classes nms_classes masks nms_masks proto nms_proto \
--output_onnx_file_path yolact_edge_mobilenetv2_550x550.onnx



sor4onnx \
--input_onnx_file_path yolact_edge_mobilenetv2_550x550.onnx \
--old_new "put" "input" \
--output_onnx_file_path yolact_edge_mobilenetv2_550x550.onnx \
--mode inputs

sor4onnx \
--input_onnx_file_path yolact_edge_mobilenetv2_550x550.onnx \
--old_new "post_x1y1x2y2_scores_classes_masks_4x1x1x32" "x1y1x2y2_scores_classes_masks_4x1x1x32" \
--output_onnx_file_path yolact_edge_mobilenetv2_550x550.onnx \
--mode outputs

sor4onnx \
--input_onnx_file_path yolact_edge_mobilenetv2_550x550.onnx \
--old_new "post_proto_out" "proto_out" \
--output_onnx_file_path yolact_edge_mobilenetv2_550x550.onnx \
--mode outputs

onnxsim yolact_edge_mobilenetv2_550x550.onnx yolact_edge_mobilenetv2_550x550.onnx
onnxsim yolact_edge_mobilenetv2_550x550.onnx yolact_edge_mobilenetv2_550x550.onnx



$INTEL_OPENVINO_DIR/deployment_tools/model_optimizer/mo.py \
--input_model yolact_edge_mobilenetv2_550x550.onnx \
--data_type FP32 \
--output_dir yolact_edge_mobilenetv2_550x550/openvino/FP32 \
--model_name yolact_edge_mobilenetv2_550x550

$INTEL_OPENVINO_DIR/deployment_tools/model_optimizer/mo.py \
--input_model yolact_edge_mobilenetv2_550x550.onnx \
--data_type FP16 \
--output_dir yolact_edge_mobilenetv2_550x550/openvino/FP16 \
--model_name yolact_edge_mobilenetv2_550x550

mkdir -p yolact_edge_mobilenetv2_550x550/openvino/myriad
${INTEL_OPENVINO_DIR}/deployment_tools/inference_engine/lib/intel64/myriad_compile \
-m yolact_edge_mobilenetv2_550x550/openvino/FP16/yolact_edge_mobilenetv2_550x550.xml \
-ip U8 \
-VPU_NUMBER_OF_SHAVES 6 \
-VPU_NUMBER_OF_CMX_SLICES 6 \
-o yolact_edge_mobilenetv2_550x550/openvino/myriad/yolact_edge_mobilenetv2_550x550.blob




New method #####################################################################################

############ xyxy -> yxyx
python nms_yolact_edge_xyxyx_yxyx.py

docker run --gpus all -it --rm \
-v `pwd`:/home/user/workdir \
ghcr.io/pinto0309/tflite2tensorflow:latest


tflite2tensorflow \
--model_path nms_yolact_edge_xyxy_yxyx.tflite \
--flatc_path ../flatc \
--schema_path ../schema.fbs \
--output_pb \
--optimizing_for_openvino_and_myriad

tflite2tensorflow \
--model_path nms_yolact_edge_xyxy_yxyx.tflite \
--flatc_path ../flatc \
--schema_path ../schema.fbs \
--output_onnx \
--onnx_opset 11

mv saved_model/model_float32.onnx nms_yolact_edge_xyxy_yxyx.onnx

onnxsim nms_yolact_edge_xyxy_yxyx.onnx nms_yolact_edge_xyxy_yxyx.onnx
onnxsim nms_yolact_edge_xyxy_yxyx.onnx nms_yolact_edge_xyxy_yxyx.onnx
onnxsim nms_yolact_edge_xyxy_yxyx.onnx nms_yolact_edge_xyxy_yxyx.onnx
onnxsim nms_yolact_edge_xyxy_yxyx.onnx nms_yolact_edge_xyxy_yxyx.onnx

sor4onnx \
--input_onnx_file_path nms_yolact_edge_xyxy_yxyx.onnx \
--old_new "Identity" "boxes_xyxy_var" \
--output_onnx_file_path nms_yolact_edge_xyxy_yxyx.onnx \
--mode outputs

############ NMS
sog4onnx \
--op_type Constant \
--opset 11 \
--op_name max_output_boxes_per_class_const \
--output_variables max_output_boxes_per_class int64 [1] \
--attributes value int64 [20] \
--output_onnx_file_path Constant_max_output_boxes_per_class.onnx

sog4onnx \
--op_type Constant \
--opset 11 \
--op_name iou_threshold_const \
--output_variables iou_threshold float32 [1] \
--attributes value float32 [0.5] \
--output_onnx_file_path Constant_iou_threshold.onnx

sog4onnx \
--op_type Constant \
--opset 11 \
--op_name score_threshold_const \
--output_variables score_threshold float32 [1] \
--attributes value float32 [0.4] \
--output_onnx_file_path Constant_score_threshold.onnx


OP=NonMaxSuppression
LOWEROP=${OP,,}
NUM_BATCHES=1
SPATIAL_DIMENSION=19248
NUM_CLASSES=80
OPSET=11
sog4onnx \
--op_type ${OP} \
--opset ${OPSET} \
--op_name ${LOWEROP}${OPSET} \
--input_variables boxes_var float32 [${NUM_BATCHES},${SPATIAL_DIMENSION},4] \
--input_variables scores_var float32 [${NUM_BATCHES},${NUM_CLASSES},${SPATIAL_DIMENSION}] \
--input_variables max_output_boxes_per_class_var int64 [1] \
--input_variables iou_threshold_var float32 [1] \
--input_variables score_threshold_var float32 [1] \
--output_variables selected_indices int64 [\'N\',3] \
--attributes center_point_box int64 0 \
--output_onnx_file_path ${OP}${OPSET}.onnx


snc4onnx \
--input_onnx_file_paths Constant_max_output_boxes_per_class.onnx NonMaxSuppression11.onnx \
--srcop_destop max_output_boxes_per_class max_output_boxes_per_class_var \
--output_onnx_file_path NonMaxSuppression11.onnx

snc4onnx \
--input_onnx_file_paths Constant_iou_threshold.onnx NonMaxSuppression11.onnx \
--srcop_destop iou_threshold iou_threshold_var \
--output_onnx_file_path NonMaxSuppression11.onnx

snc4onnx \
--input_onnx_file_paths Constant_score_threshold.onnx NonMaxSuppression11.onnx \
--srcop_destop score_threshold score_threshold_var \
--output_onnx_file_path NonMaxSuppression11.onnx



############ myriad workaround Mul
OP=Mul
LOWEROP=${OP,,}
NUM_BATCHES=1
OPSET=11
sog4onnx \
--op_type ${OP} \
--opset ${OPSET} \
--op_name ${LOWEROP}${OPSET} \
--input_variables workaround_mul_a int64 [\'N\',3] \
--input_variables workaround_mul_b int64 [1] \
--output_variables workaround_mul_out int64 [\'N\',3] \
--output_onnx_file_path ${OP}${OPSET}_workaround.onnx

############ myriad workaround Constant
sog4onnx \
--op_type Constant \
--opset 11 \
--op_name workaround_mul_const_op \
--output_variables workaround_mul_const int64 [1] \
--attributes value int64 [1] \
--output_onnx_file_path Constant_workaround_mul.onnx

############ myriad workaround Mul + myriad workaround Constant
snc4onnx \
--input_onnx_file_paths Constant_workaround_mul.onnx Mul11_workaround.onnx \
--srcop_destop workaround_mul_const workaround_mul_b \
--output_onnx_file_path Mul11_workaround.onnx



############ NMS + myriad workaround Mul
snc4onnx \
--input_onnx_file_paths NonMaxSuppression11.onnx Mul11_workaround.onnx \
--srcop_destop selected_indices workaround_mul_a \
--output_onnx_file_path NonMaxSuppression11.onnx


############ yxyx + NMS
snc4onnx \
--input_onnx_file_paths nms_yolact_edge_xyxy_yxyx.onnx NonMaxSuppression11.onnx \
--srcop_destop boxes_xyxy_var boxes_var \
--output_onnx_file_path NonMaxSuppression11.onnx

sor4onnx \
--input_onnx_file_path NonMaxSuppression11.onnx \
--old_new "input_1" "boxes_var" \
--output_onnx_file_path NonMaxSuppression11.onnx \
--mode inputs


############ NMS Slice
python nms_yolact_edge_score_indices.py

python -m tf2onnx.convert \
--opset 11 \
--tflite saved_model_postprocess/nms_yolact_edge_score_indices.tflite \
--output nms_yolact_edge_score_indices.onnx

onnxsim nms_yolact_edge_score_indices.onnx nms_yolact_edge_score_indices.onnx
onnxsim nms_yolact_edge_score_indices.onnx nms_yolact_edge_score_indices.onnx

sor4onnx \
--input_onnx_file_path nms_yolact_edge_score_indices.onnx \
--old_new "Identity_1" "box_indices_sliced" \
--output_onnx_file_path nms_yolact_edge_score_indices.onnx \
--mode outputs

sor4onnx \
--input_onnx_file_path nms_yolact_edge_score_indices.onnx \
--old_new "Identity" "classes_sliced" \
--output_onnx_file_path nms_yolact_edge_score_indices.onnx \
--mode outputs

sor4onnx \
--input_onnx_file_path nms_yolact_edge_score_indices.onnx \
--old_new "input_1" "selected_indices_before_slice" \
--output_onnx_file_path nms_yolact_edge_score_indices.onnx \
--mode inputs


############ Boxes gather
OP=Gather
LOWEROP=${OP,,}
NUM_BATCHES=1
SPATIAL_DIMENSION=19248
OPSET=11
sog4onnx \
--op_type ${OP} \
--opset ${OPSET} \
--op_name ${LOWEROP}${OPSET}_boxes \
--input_variables gat_boxes_var float32 [${NUM_BATCHES},${SPATIAL_DIMENSION},4] \
--input_variables gat_boxes_indices_var int64 [\'N\'] \
--output_variables gat_boxes_out float32 [${NUM_BATCHES},\'N\',4] \
--attributes axis int64 1 \
--output_onnx_file_path ${OP}${OPSET}_boxes.onnx

onnxsim ${OP}${OPSET}_boxes.onnx ${OP}${OPSET}_boxes.onnx

############ Masks gather
OP=Gather
LOWEROP=${OP,,}
NUM_BATCHES=1
SPATIAL_DIMENSION=19248
OPSET=11
sog4onnx \
--op_type ${OP} \
--opset ${OPSET} \
--op_name ${LOWEROP}${OPSET}_masks \
--input_variables gat_masks_var float32 [${NUM_BATCHES},${SPATIAL_DIMENSION},32] \
--input_variables gat_masks_indices_var int64 [\'N\'] \
--output_variables gat_masks_out float32 [${NUM_BATCHES},\'N\',32] \
--attributes axis int64 1 \
--output_onnx_file_path ${OP}${OPSET}_masks.onnx

onnxsim ${OP}${OPSET}_masks.onnx ${OP}${OPSET}_masks.onnx



############ NMS Slice + Boxes gather
snc4onnx \
--input_onnx_file_paths nms_yolact_edge_score_indices.onnx Gather11_boxes.onnx \
--srcop_destop box_indices_sliced gat_boxes_indices_var \
--output_onnx_file_path nms_yolact_edge_score_indices.onnx

############ NMS Slice + Masks gather
snc4onnx \
--input_onnx_file_paths nms_yolact_edge_score_indices.onnx Gather11_masks.onnx \
--srcop_destop box_indices_sliced gat_masks_indices_var \
--output_onnx_file_path nms_yolact_edge_score_indices.onnx


############ NMS + Sliced values
snc4onnx \
--input_onnx_file_paths NonMaxSuppression11.onnx nms_yolact_edge_score_indices.onnx \
--srcop_destop workaround_mul_out selected_indices_before_slice boxes_var gat_boxes_var \
--op_prefixes_after_merging fnms snms \
--output_onnx_file_path NonMaxSuppression11.onnx


############ proto squeeze
OP=Squeeze
LOWEROP=${OP,,}
NUM_BATCHES=1
H=138
W=138
OPSET=11
sog4onnx \
--op_type ${OP} \
--opset ${OPSET} \
--op_name ${LOWEROP}${OPSET}_proto \
--input_variables squeeze_proto_var float32 [${NUM_BATCHES},${H},${W},32] \
--output_variables squeeze_proto_out float32 [${H},${W},32] \
--attributes axes int64 [0] \
--output_onnx_file_path ${OP}${OPSET}_proto.onnx
onnxsim ${OP}${OPSET}_proto.onnx ${OP}${OPSET}_proto.onnx

############ Base model proto + proto squeeze
snc4onnx \
--input_onnx_file_paths yolact_edge_mobilenetv2_54_800000.onnx Squeeze11_proto.onnx \
--srcop_destop proto squeeze_proto_var \
--output_onnx_file_path yolact_edge_mobilenetv2_54_800000.onnx
onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx


############ Base model + NMS
snc4onnx \
--input_onnx_file_paths yolact_edge_mobilenetv2_54_800000.onnx NonMaxSuppression11.onnx \
--srcop_destop boxes fnms_boxes_var scores fnms_scores_var masks snms_gat_masks_var \
--output_onnx_file_path yolact_edge_mobilenetv2_54_800000.onnx
onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx


############ snms_gat_masks_out squeeze
OP=Squeeze
LOWEROP=${OP,,}
NUM_BATCHES=1
OPSET=11
sog4onnx \
--op_type ${OP} \
--opset ${OPSET} \
--op_name ${LOWEROP}${OPSET}_snms_squeeze_masks_out \
--input_variables squeeze_snms_squeeze_masks_out_var float32 [${NUM_BATCHES},\'N\',32] \
--output_variables squeeze_snms_squeeze_masks_out float32 [\'N\',32] \
--attributes axes int64 [0] \
--output_onnx_file_path ${OP}${OPSET}_snms_squeeze_masks_out.onnx
onnxsim ${OP}${OPSET}_snms_squeeze_masks_out.onnx ${OP}${OPSET}_snms_squeeze_masks_out.onnx


############ Base model proto + proto squeeze
snc4onnx \
--input_onnx_file_paths yolact_edge_mobilenetv2_54_800000.onnx Squeeze11_snms_squeeze_masks_out.onnx \
--srcop_destop snms_gat_masks_out squeeze_snms_squeeze_masks_out_var \
--output_onnx_file_path yolact_edge_mobilenetv2_54_800000.onnx
onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx



############ Score gather
python nms_yolact_edge_score_gather_nd.py

python -m tf2onnx.convert \
--opset 11 \
--tflite saved_model_postprocess/nms_yolact_edge_score_gather_nd.tflite \
--output nms_yolact_edge_score_gather_nd.onnx

onnxsim nms_yolact_edge_score_gather_nd.onnx nms_yolact_edge_score_gather_nd.onnx
onnxsim nms_yolact_edge_score_gather_nd.onnx nms_yolact_edge_score_gather_nd.onnx

sor4onnx \
--input_onnx_file_path nms_yolact_edge_score_gather_nd.onnx \
--old_new "input_1" "score_gather_nd_input" \
--output_onnx_file_path nms_yolact_edge_score_gather_nd.onnx \
--mode inputs

sor4onnx \
--input_onnx_file_path nms_yolact_edge_score_gather_nd.onnx \
--old_new "input_2" "score_gather_nd_indices" \
--output_onnx_file_path nms_yolact_edge_score_gather_nd.onnx \
--mode inputs

sor4onnx \
--input_onnx_file_path nms_yolact_edge_score_gather_nd.onnx \
--old_new "Identity" "final_scores" \
--output_onnx_file_path nms_yolact_edge_score_gather_nd.onnx \
--mode outputs

############ Base model + Score gather
snc4onnx \
--input_onnx_file_paths yolact_edge_mobilenetv2_54_800000.onnx nms_yolact_edge_score_gather_nd.onnx \
--srcop_destop scores score_gather_nd_input fnms_selected_indices score_gather_nd_indices \
--output_onnx_file_path yolact_edge_mobilenetv2_54_800000.onnx
onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx



############ Base model 3 outputs concat
OP=Concat
LOWEROP=${OP,,}
NUM_BATCHES=1
OPSET=11
sog4onnx \
--op_type ${OP} \
--opset ${OPSET} \
--op_name ${LOWEROP}${OPSET}_final_concat \
--input_variables cfinal_boxes float32 [${NUM_BATCHES},\'N\',4] \
--input_variables cfinal_scores float32 [${NUM_BATCHES},\'N\',1] \
--input_variables cfinal_classes float32 [${NUM_BATCHES},\'N\',1] \
--output_variables x1y1x2y2_score_class float32 [${NUM_BATCHES},\'N\',6] \
--attributes axis int64 2 \
--output_onnx_file_path ${OP}${OPSET}_final_concat.onnx
onnxsim ${OP}${OPSET}_final_concat.onnx ${OP}${OPSET}_final_concat.onnx


############ Base model + Final concat
snc4onnx \
--input_onnx_file_paths yolact_edge_mobilenetv2_54_800000.onnx Concat11_final_concat.onnx \
--srcop_destop snms_gat_boxes_out cfinal_boxes final_scores cfinal_scores snms_classes_sliced cfinal_classes \
--output_onnx_file_path yolact_edge_mobilenetv2_54_800000.onnx
onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx


############ Mask Transpose
sog4onnx \
--op_type Transpose \
--opset 11 \
--op_name mask_transpose \
--input_variables mask_trans_input float32 [\'N\',32] \
--output_variables mask_trans_output float32 [32,\'N\'] \
--attributes perm int64 [1,0] \
--output_onnx_file_path Transpose11_mask_transpose.onnx

############ Base model + Mask Transpose
snc4onnx \
--input_onnx_file_paths yolact_edge_mobilenetv2_54_800000.onnx Transpose11_mask_transpose.onnx \
--srcop_destop squeeze_snms_squeeze_masks_out mask_trans_input \
--output_onnx_file_path yolact_edge_mobilenetv2_54_800000.onnx
onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx



############ Mask MatMul
sog4onnx \
--op_type MatMul \
--opset 11 \
--op_name mask_matmul \
--input_variables mask_matmul_input_a float32 [138,138,32] \
--input_variables mask_matmul_input_b float32 [32,\'N\'] \
--output_variables mask_matmul_output float32 [138,138,\'N\'] \
--output_onnx_file_path MatMul11_mask_matmul.onnx
onnxsim MatMul11_mask_matmul.onnx MatMul11_mask_matmul.onnx

############ Base model + Mask MatMul
snc4onnx \
--input_onnx_file_paths yolact_edge_mobilenetv2_54_800000.onnx MatMul11_mask_matmul.onnx \
--srcop_destop squeeze_proto_out mask_matmul_input_a mask_trans_output mask_matmul_input_b \
--output_onnx_file_path yolact_edge_mobilenetv2_54_800000.onnx
onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx


############ Mask Sigmoid
sog4onnx \
--op_type Sigmoid \
--opset 11 \
--op_name mask_sigmoid \
--input_variables mask_sig_input float32 [138,138,\'N\'] \
--output_variables mask_sig_output float32 [138,138,\'N\'] \
--output_onnx_file_path Sigmoid11_mask_sigmoid.onnx
onnxsim Sigmoid11_mask_sigmoid.onnx Sigmoid11_mask_sigmoid.onnx

############ Base model + Mask Sigmoid
snc4onnx \
--input_onnx_file_paths yolact_edge_mobilenetv2_54_800000.onnx Sigmoid11_mask_sigmoid.onnx \
--srcop_destop mask_matmul_output mask_sig_input \
--output_onnx_file_path yolact_edge_mobilenetv2_54_800000.onnx
onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx


############ Mask Final Transpose
sog4onnx \
--op_type Transpose \
--opset 11 \
--op_name mask_final_transpose \
--input_variables mask_final_trans_input float32 [138,138,\'N\'] \
--output_variables final_masks float32 [\'N\',138,138] \
--attributes perm int64 [2,0,1] \
--output_onnx_file_path Transpose11_mask_final_transpose.onnx

############ Base model + Mask Final Transpose
snc4onnx \
--input_onnx_file_paths yolact_edge_mobilenetv2_54_800000.onnx Transpose11_mask_final_transpose.onnx \
--srcop_destop mask_sig_output mask_final_trans_input \
--output_onnx_file_path yolact_edge_mobilenetv2_54_800000.onnx
onnxsim yolact_edge_mobilenetv2_54_800000.onnx yolact_edge_mobilenetv2_54_800000.onnx