opencv-python(cv2)显示图片&图片显示不了问题
opencv
OpenCV: 开源计算机视觉库
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我之前刚开始玩openCV时,遇到了图像显示不了的问题,主要报下面的错误:
error: (-215:Assertion failed) !_src.empty() in function 'cv::cvtColor'
error: (-215:Assertion failed) size.width>0 && size.height>0 in function 'cv::imshow'
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1、首先,将图片路径更换为绝对路径
2、若改为绝对路径后还不行,请检查路径的格式(有没有多或少标点)
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(1)、如果你是在windows中直接复制的路径,那你或许要把路径中的分隔符 “ \ ” 改为 “ / ”;
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(2)、如果你是在Linux系统中,记得在路径的最前面加上 " / " ,例如:"/var/www"
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(3)、也与可能是你路径存在中文字符
总之,要不就是你的文件不存在,要不就是你的路径错了;
GitHub 加速计划 / opencv31 / opencv
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OpenCV: 开源计算机视觉库
最近提交(Master分支:2 个月前 )
35571be5
Use LMUL=2 in the RISC-V Vector (RVV) backend of Universal Intrinsic. #26318
The modification of this patch involves the RVV backend of Universal Intrinsic, replacing `LMUL=1` with `LMUL=2`.
Now each Universal Intrinsic type actually corresponds to two RVV vector registers, and each Intrinsic function also operates two vector registers. Considering that algorithms written using Universal Intrinsic usually do not use the maximum number of registers, this can help the RVV backend utilize more register resources without modifying the algorithm implementation
This patch is generally beneficial in performance.
We compiled OpenCV with `Clang-19.1.1` and `GCC-14.2.0` , ran it on `CanMV-k230` and `Banana-Pi F3`. Then we have four scenarios on combinations of compilers and devices. In `opencv_perf_core`, there are 3363 cases, of which:
- 901 (26.8%) cases achieved more than `5%` performance improvement in all four scenarios, and the average speedup of these test cases (compared to scalar) increased from `3.35x` to `4.35x`
- 75 (2.2%) cases had more than `5%` performance loss in all four scenarios, indicating that these cases are better with `LMUL=1` instead of `LMUL=2`. This involves `Mat_Transform`, `hasNonZero`, `KMeans`, `meanStdDev`, `merge` and `norm2`. Among them, `Mat_Transform` only has performance degradation in a few cases (`8UC3`), and the actual execution time of `hasNonZero` is so short that it can be ignored. For `KMeans`, `meanStdDev`, `merge` and `norm2`, we should be able to use the HAL to optimize/restore their performance. (In fact, we have already done this for `merge` #26216 )
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
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