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annoseg's Introduction

Hi there 👋

I'm Zhongying, a computer science grad with a knack for all things engineering. From diving into out-of-distribution detection at Hikvision to cracking the code on storage systems at Huawei, I've honed my engineering prowess. During my stint at Nutshell Therapeutics, I rocked algorithm reproduction and bioinformatics, showcasing my knack for quick learning. Now, as an Algorithm Engineer at Sophgo, I'm in the thick of business tool development and AI algorithm adaption– truly flexing my engineering muscles. I'm all about staying ahead of the curve, soaking up the latest AI trends, and infusing them into real-world projects. Ready to connect, collaborate, and drive innovation in tech! 🚀 (Generated by GPT3.5)

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annoseg's Issues

报错

已解决，成功运行，处理视频速度并不快

模型替换

你好，我现在正在复现这个例程，YOLO的部分我已经复现成功。请问SAM的bmodel有没有具体的转换教程？

mobilesam与BM1684X

81E425F5-EC0C-48EB-B762-950BF72CD37A

你好，你这个项目使用的是mobilesam tinyViT(5.78M)吗？我看到你们已经转了模型，运行在BM1684X上了，能方便提供一下转模型的指引吗？我想把mobilesam ViT-H(632M)转模型，让vit-h跑在BM1684X上，谢谢！

网络摄像头？

请问程序中似乎没有关于网络摄像头调用的部分，如果我要处理实时画面，是否需要自己修改程序呢？我需要怎么做？

mobilesam_encoder.onnx转bmodel错误

请问我在尝试复现时，mask_decoder和sam_vit_h都成功转出了bmodel，但在mobilesam的encoder转换时报了如下错误：
Traceback (most recent call last): File "/workspace/python/tools/model_deploy.py", line 344, in <module> tool.build_model() File "/workspace/python/tools/model_deploy.py", line 235, in build_model mlir_to_model(self.tpu_mlir, self.model, self.final_mlir, self.dynamic, File "/workspace/python/utils/mlir_shell.py", line 172, in mlir_to_model _os_system(cmd) File "/workspace/python/utils/mlir_shell.py", line 50, in _os_system raise RuntimeError("[!Error]: {}".format(cmd_str)) RuntimeError: [!Error]: tpuc-opt mobile_sam_bm1684x_f16_final.mlir --codegen="model_file=mobile_sam_fp16.bmodel embed_debug_info=false model_version=latest" -o /dev/null

请问这是为什么，我是尝试转BM1864X的fp32的模型，所使用的命令如下：
onnx转mlir：
model_transform.py --model_name mobile_sam --model_def mobile_sam.onnx --input_shapes [1024,1024,3] --mlir mobile_sam.mlir
mlir转bmodel：（错误发生在这一步）
model_deploy.py --mlir mobile_sam.mlir --quantize F16 --chip bm1684x --model mobile_sam_fp16.bmodel

希望得到解答，感谢！

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