HoangTienDuc
commented
1 year ago Hi Katsuya, Thanks for your reply. I only run the sample "convert_script.txt" from 307_yolov7/post_process_gen_tools
Reproduce:
OPSET=11
BATCHES=1
BOXES=5040
CLASSES=80
################################################### Boxes + Scores
python make_boxes_scores.py -o ${OPSET} -b ${BATCHES} -x ${BOXES} -c
${CLASSES}
python make_cxcywh_y1x1y2x2.py -o ${OPSET} -b ${BATCHES} -x ${BOXES}
snc4onnx \
--input_onnx_file_paths boxes_scores_${BOXES}.onnx
cxcywh_y1x1y2x2_${BOXES}.onnx \
--srcop_destop boxes_cxcywh cxcywh \
--output_onnx_file_path boxes_y1x1y2x2_scores_${BOXES}.onnx
################################################### NonMaxSuppression
sog4onnx \
--op_type Constant \
--opset ${OPSET} \
--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 ${OPSET} \
--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 ${OPSET} \
--op_name score_threshold_const \
--output_variables score_threshold float32 [1] \
--attributes value float32 [0.4] \
--output_onnx_file_path Constant_score_threshold.onnx
OP=NonMaxSuppression
LOWEROP=${OP,,}
sog4onnx \
--op_type ${OP} \
--opset ${OPSET} \
--op_name ${LOWEROP}${OPSET} \
--input_variables boxes_var float32 [${BATCHES},${BOXES},4] \
--input_variables scores_var float32 [${BATCHES},${CLASSES},${BOXES}] \
--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 NonMaxSuppression${OPSET}.onnx
snc4onnx \
--input_onnx_file_paths Constant_iou_threshold.onnx
NonMaxSuppression${OPSET}.onnx \
--srcop_destop iou_threshold iou_threshold_var \
--output_onnx_file_path NonMaxSuppression${OPSET}.onnx
snc4onnx \
--input_onnx_file_paths Constant_score_threshold.onnx
NonMaxSuppression${OPSET}.onnx \
--srcop_destop score_threshold score_threshold_var \
--output_onnx_file_path NonMaxSuppression${OPSET}.onnx
soc4onnx \
--input_onnx_file_path NonMaxSuppression${OPSET}.onnx \
--output_onnx_file_path NonMaxSuppression${OPSET}.onnx \
--opset ${OPSET}
################################################### Boxes + Scores +
NonMaxSuppression
snc4onnx \
--input_onnx_file_paths boxes_y1x1y2x2_scores_${BOXES}.onnx
NonMaxSuppression${OPSET}.onnx \
--srcop_destop scores scores_var y1x1y2x2 boxes_var \
--output_onnx_file_path nms_yolov7_${BOXES}.onnx
################################################### Myriad workaround Mul
OP=Mul
LOWEROP=${OP,,}
OPSET=${OPSET}
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 ${OPSET} \
--op_name workaround_mul_const_op \
--output_variables workaround_mul_const int64 [1] \
--attributes value int64 [1] \
--output_onnx_file_path Constant_workaround_mul.onnx
############ Myriad workaround Mul + Myriad workaround Constant
snc4onnx \
--input_onnx_file_paths Constant_workaround_mul.onnx
Mul${OPSET}_workaround.onnx \
--srcop_destop workaround_mul_const workaround_mul_b \
--output_onnx_file_path Mul${OPSET}_workaround.onnx
################################################### NonMaxSuppression +
Myriad workaround Mul
snc4onnx \
--input_onnx_file_paths nms_yolov7_${BOXES}.onnx
Mul${OPSET}_workaround.onnx \
--srcop_destop selected_indices workaround_mul_a \
--output_onnx_file_path nms_yolov7_${BOXES}.onnx
################################################### Score GatherND
python make_score_gather_nd.py -b ${BATCHES} -x ${BOXES} -c ${CLASSES}
python -m tf2onnx.convert \
--opset ${OPSET} \
--tflite saved_model_postprocess/nms_score_gather_nd.tflite \
--output nms_score_gather_nd.onnx
sor4onnx \
--input_onnx_file_path nms_score_gather_nd.onnx \
--old_new ":0" "" \
--output_onnx_file_path nms_score_gather_nd.onnx
sor4onnx \
--input_onnx_file_path nms_score_gather_nd.onnx \
--old_new "serving_default_input_1" "gn_scores" \
--output_onnx_file_path nms_score_gather_nd.onnx \
--mode inputs
sor4onnx \
--input_onnx_file_path nms_score_gather_nd.onnx \
--old_new "serving_default_input_2" "gn_selected_indices" \
--output_onnx_file_path nms_score_gather_nd.onnx \
--mode inputs
sor4onnx \
--input_onnx_file_path nms_score_gather_nd.onnx \
--old_new "PartitionedCall" "final_scores" \
--output_onnx_file_path nms_score_gather_nd.onnx \
--mode outputs
python make_input_output_shape_update.py \
--input_onnx_file_path nms_score_gather_nd.onnx \
--output_onnx_file_path nms_score_gather_nd.onnx \
--input_names gn_scores \
--input_names gn_selected_indices \
--input_shapes ${BATCHES} ${CLASSES} ${BOXES} \
--input_shapes N 3 \
--output_names final_scores \
--output_shapes N 1On Sun, Aug 20, 2023 at 12:28 PM Katsuya Hyodo @.***> wrote:
KeyError: 'serving_default_input_1:0' is displayed. That's all there is to it. How would I know what model you are using?
— Reply to this email directly, view it on GitHub https://github.com/PINTO0309/PINTO_model_zoo/issues/358#issuecomment-1685181593, or unsubscribe https://github.com/notifications/unsubscribe-auth/AMWDRMRIZ42A7M5WQBQLSO3XWGOADANCNFSM6AAAAAA3WKOJDY . You are receiving this because you authored the thread.Message ID: @.***>
PINTO0309
Issue Type
Bug
OS
Ubuntu
OS architecture
x86_64
Programming Language
Python
Framework
TensorFlow, TensorFlowLite
Model name and Weights/Checkpoints URL
Model name: yolov7 https://github.com/PINTO0309/PINTO_model_zoo/tree/18e75913cb97eefa2d8fe9f87b86841407b4c826/307_YOLOv7/post_process_gen_tools
Description
Hi PINTO, your work is awesome. I try to replicate your work to post-process my custon yolov7 model. First, i tried to follow the instruction from your model zoo yolov7 post-process without any change, but with your original postprocess docker (1.1.5, 1.1.15), i cannot "update_model_dims.update_inputs_outputs_dims". Tried with diffirent dockers, tf2onnx, tensorflow version, but it is still not work. Can you pls give me some advice? Thanks
Relevant Log Output
URL or source code for simple inference testing code
No response