we need remove Mod Xor Not op inside onnx

export_onnx.py

@@ -239,8 +239,8 @@ def vis_res_fast(res, img, colors):
 
 def get_model_infos(config_file):
     if "sparse_inst" in config_file:
-        # output_names = ["masks", "scores", "labels"]
-        output_names = ["masks", "scores"]
+        output_names = ["masks", "scores", "labels"]
+        # output_names = ["masks", "scores"]
         input_names = ["images"]
         dynamic_axes = {"images": {0: "batch"}}
         return input_names, output_names, dynamic_axes
@@ -291,7 +291,7 @@ def get_model_infos(config_file):
         onnx_f,
         input_names=input_names,
         output_names=output_names,
-        opset_version=12,
+        opset_version=11,
         do_constant_folding=True,
         verbose=args.verbose,
         dynamic_axes=dynamic_axes,

readme.md

@@ -212,6 +212,11 @@ Make sure you have read **rules** before ask me any questions.
 3. `SparseInst`:
    Sparsinst already supported exporting to onnx!!
 
+  ```
+  python export_onnx.py --config-file configs/coco/sparseinst/sparse_inst_r50_giam_aug.yaml --video-input ~/Videos/a.flv  --opts MODEL.WEIGHTS weights/sparse_inst_r50_giam_aug_2b7d68.pth INPUT.MIN_SIZE_TEST 512
+  ```
+  Then you can have `weights/sparse_inst_r50_giam_aug_2b7d68_sim.onnx` generated, this onnx can be inference using ORT without any unsupported ops.
+
 
 
 ## 🤒️ Performance

yolov7/modeling/meta_arch/sparseinst.py

@@ -266,5 +266,5 @@ def inference_onnx(self, output, batched_inputs, max_shape):
         # logger.info(f'all_scores: {all_scores.shape}')
         # logger.info(f'all_labels: {all_labels.shape}')
         logger.info(f'all_masks: {all_masks.shape}')
-        return all_masks, all_scores
+        return all_masks, all_scores, all_labels
         # return all_masks, all_labels