piddnad / ddcolor Goto Github PK
View Code? Open in Web Editor NEW[ICCV 2023] DDColor: Towards Photo-Realistic Image Colorization via Dual Decoders
License: Apache License 2.0
[ICCV 2023] DDColor: Towards Photo-Realistic Image Colorization via Dual Decoders
License: Apache License 2.0
可以用于视频修复吗
At first I use python=3.8
which as told from https://github.com/piddnad/DDColor, but got error like below
ERROR: Ignored the following yanked versions: 0.20.0.dev0, 0.20.0rc2, 0.20.0rc3, 0.20.0rc6, 0.20.0rc7
ERROR: Ignored the following versions that require a different python version: 0.22.0 Requires-Python >=3.9; 0.22.0rc1 Requires-Python >=3.9; 0.23.0 Requires-Python >=3.10; 0.23.0rc0 Requires-Python >=3.10; 0.23.0rc2 Requires-Python >=3.10; 0.23.1 Requires-Python >=3.10; 0.23.2 Requires-Python >=3.10; 0.23.2rc1 Requires-Python >=3.10; 1.11.0 Requires-Python <3.13,>=3.9; 1.11.0rc1 Requires-Python <3.13,>=3.9; 1.11.0rc2 Requires-Python <3.13,>=3.9; 1.11.1 Requires-Python <3.13,>=3.9; 1.11.2 Requires-Python <3.13,>=3.9; 1.11.3 Requires-Python <3.13,>=3.9; 1.11.4 Requires-Python >=3.9; 1.12.0 Requires-Python >=3.9; 1.12.0rc1 Requires-Python >=3.9; 1.12.0rc2 Requires-Python >=3.9; 1.13.0 Requires-Python >=3.9; 1.13.0rc1 Requires-Python >=3.9; 1.25.0 Requires-Python >=3.9; 1.25.0rc1 Requires-Python >=3.9; 1.25.1 Requires-Python >=3.9; 1.25.2 Requires-Python >=3.9; 1.26.0 Requires-Python <3.13,>=3.9; 1.26.0b1 Requires-Python <3.13,>=3.9; 1.26.0rc1 Requires-Python <3.13,>=3.9; 1.26.1 Requires-Python <3.13,>=3.9; 1.26.2 Requires-Python >=3.9; 1.26.3 Requires-Python >=3.9; 1.26.4 Requires-Python >=3.9; 2.0.0b1 Requires-Python >=3.9; 2.0.0rc1 Requires-Python >=3.9
ERROR: Could not find a version that satisfies the requirement scikit-image==0.22.0 (from versions: 0.7.2, 0.8.0, 0.8.1, 0.8.2, 0.9.0, 0.9.1, 0.9.3, 0.10.0, 0.10.1, 0.11.2, 0.11.3, 0.12.0, 0.12.1, 0.12.2, 0.12.3, 0.13.0, 0.13.1, 0.14.0, 0.14.1, 0.14.2, 0.14.3, 0.14.5, 0.15.0, 0.16.2, 0.17.1, 0.17.2, 0.18.0, 0.18.1, 0.18.2, 0.18.3, 0.19.0rc0, 0.19.0, 0.19.1, 0.19.2, 0.19.3, 0.20.0rc4, 0.20.0rc5, 0.20.0rc8, 0.20.0, 0.21.0rc0, 0.21.0rc1, 0.21.0)
ERROR: No matching distribution found for scikit-image==0.22.0
I realized maybe the python version is low, so i changed into 'python3.10' beacuase the erros msg said Requires-Python >=3.10
but still error like below
Building wheels for collected packages: dlib
Building wheel for dlib (pyproject.toml) ... error
error: subprocess-exited-with-error
× Building wheel for dlib (pyproject.toml) did not run successfully.
│ exit code: 1
╰─> [73 lines of output]
running bdist_wheel
running build
running build_ext
<string>:125: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
Building extension for Python 3.10.14 | packaged by Anaconda, Inc. | (main, Mar 21 2024, 16:20:14) [MSC v.1916 64 bit (AMD64)]
Invoking CMake setup: 'cmake C:\Users\shadow\AppData\Local\Temp\pip-install-373trf7q\dlib_669ba91aa7214a9eb95805ba13046fd7\tools\python -DCMAKE_LIBRARY_OUTPUT_DIRECTORY=C:\Users\shadow\AppData\Local\Temp\pip-install-373trf7q\dlib_669ba91aa7214a9eb95805ba13046fd7\build\lib.win-amd64-cpython-310 -DPYTHON_EXECUTABLE=D:\soft\miniconda3\envs\python310\python.exe -DCMAKE_LIBRARY_OUTPUT_DIRECTORY_RELEASE=C:\Users\shadow\AppData\Local\Temp\pip-install-373trf7q\dlib_669ba91aa7214a9eb95805ba13046fd7\build\lib.win-amd64-cpython-310 -A x64'
-- Building for: NMake Makefiles
CMake Error at CMakeLists.txt:5 (message):
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
You must use Visual Studio to build a python extension on windows. If you
are getting this error it means you have not installed Visual C++. Note
that there are many flavors of Visual Studio, like Visual Studio for C#
development. You need to install Visual Studio for C++.
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
-- Configuring incomplete, errors occurred!
Traceback (most recent call last):
File "D:\soft\miniconda3\envs\python310\lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 353, in <module>
main()
File "D:\soft\miniconda3\envs\python310\lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 335, in main
json_out['return_val'] = hook(**hook_input['kwargs'])
File "D:\soft\miniconda3\envs\python310\lib\site-packages\pip\_vendor\pyproject_hooks\_in_process\_in_process.py", line 251, in build_wheel
return _build_backend().build_wheel(wheel_directory, config_settings,
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\build_meta.py", line 410, in build_wheel
return self._build_with_temp_dir(
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\build_meta.py", line 395, in _build_with_temp_dir
self.run_setup()
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\build_meta.py", line 311, in run_setup
exec(code, locals())
File "<string>", line 218, in <module>
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\__init__.py", line 104, in setup
return distutils.core.setup(**attrs)
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\_distutils\core.py", line 184, in setup
return run_commands(dist)
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\_distutils\core.py", line 200, in run_commands
dist.run_commands()
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\_distutils\dist.py", line 969, in run_commands
self.run_command(cmd)
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\dist.py", line 967, in run_command
super().run_command(command)
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\_distutils\dist.py", line 988, in run_command
cmd_obj.run()
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\wheel\bdist_wheel.py", line 368, in run
self.run_command("build")
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\_distutils\cmd.py", line 316, in run_command
self.distribution.run_command(command)
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\dist.py", line 967, in run_command
super().run_command(command)
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\_distutils\dist.py", line 988, in run_command
cmd_obj.run()
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\_distutils\command\build.py", line 132, in run
self.run_command(cmd_name)
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\_distutils\cmd.py", line 316, in run_command
self.distribution.run_command(command)
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\dist.py", line 967, in run_command
super().run_command(command)
File "C:\Users\shadow\AppData\Local\Temp\pip-build-env-b5s6o_5j\overlay\Lib\site-packages\setuptools\_distutils\dist.py", line 988, in run_command
cmd_obj.run()
File "<string>", line 130, in run
File "<string>", line 167, in build_extension
File "D:\soft\miniconda3\envs\python310\lib\subprocess.py", line 369, in check_call
raise CalledProcessError(retcode, cmd)
subprocess.CalledProcessError: Command '['cmake', 'C:\\Users\\shadow\\AppData\\Local\\Temp\\pip-install-373trf7q\\dlib_669ba91aa7214a9eb95805ba13046fd7\\tools\\python', '-DCMAKE_LIBRARY_OUTPUT_DIRECTORY=C:\\Users\\shadow\\AppData\\Local\\Temp\\pip-install-373trf7q\\dlib_669ba91aa7214a9eb95805ba13046fd7\\build\\lib.win-amd64-cpython-310', '-DPYTHON_EXECUTABLE=D:\\soft\\miniconda3\\envs\\python310\\python.exe', '-DCMAKE_LIBRARY_OUTPUT_DIRECTORY_RELEASE=C:\\Users\\shadow\\AppData\\Local\\Temp\\pip-install-373trf7q\\dlib_669ba91aa7214a9eb95805ba13046fd7\\build\\lib.win-amd64-cpython-310', '-A', 'x64']' returned non-zero exit status 1.
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed building wheel for dlib
Failed to build dlib
ERROR: Could not build wheels for dlib, which is required to install pyproject.toml-based projects
So, i don't know how to fix it, somewhere wrong? Any help will be appreciated.
Hi,
Thanks for your great work! I trained a model for 400,000 iterations on one dataset, and now I want to continue training for an additional 400,000 iterations using the net_g_400000.pth model. Do I just need to change the total_iter value from 400,000 to 800,000?
Thanks!
Excuse me, can I train this on my own datasets?
When testing on the validation set of COCO Stuff, ADE20K, and ImageNet, did you first resize the input image to (512,512), and then linearly interpolate the coloring results to the original resolution?
Hi there! I really like your colorization model. I'm using it on old images and I think it works better than the other currently available options, except sometimes red color is too strong. When I run it as python script I get a couple of warnings I want to ask if there are any ways to avoid these warnings thanks!
2024-03-15 17:43:21,771 - modelscope - INFO - PyTorch version 2.2.1+rocm5.7 Found.
2024-03-15 17:43:21,797 - modelscope - INFO - Loading ast index from /home/rubing/.cache/modelscope/ast_indexer
2024-03-15 17:43:21,824 - modelscope - INFO - Loading done! Current index file version is 1.13.1, with md5 bf5a0cac5e5265c888d1b6453711fc56 and a total number of 972 components indexed
2024-03-15 17:43:25,009 - modelscope - WARNING - Model revision not specified, use revision: v1.02
2024-03-15 17:43:25,743 - modelscope - INFO - initiate model from /home/rubing/.cache/modelscope/hub/damo/cv_ddcolor_image-colorization
2024-03-15 17:43:25,745 - modelscope - INFO - initiate model from location /home/rubing/.cache/modelscope/hub/damo/cv_ddcolor_image-colorization.
2024-03-15 17:43:25,748 - modelscope - INFO - initialize model from /home/rubing/.cache/modelscope/hub/damo/cv_ddcolor_image-colorization
2024-03-15 17:43:29,373 - modelscope - INFO - Loading DDColor model from /home/rubing/.cache/modelscope/hub/damo/cv_ddcolor_image-colorization/pytorch_model.pt, with param key: [params].
2024-03-15 17:43:29,658 - modelscope - INFO - load model done.
2024-03-15 17:43:29,737 - modelscope - WARNING - No preprocessor field found in cfg.
2024-03-15 17:43:29,779 - modelscope - WARNING - No val key and type key found in preprocessor domain of configuration.json file.
2024-03-15 17:43:29,781 - modelscope - WARNING - Cannot find available config to build preprocessor at mode inference, current config: {'model_dir': '/home/rubing/.cache/modelscope/hub/damo/cv_ddcolor_image-colorization'}. trying to build by task and model information.
2024-03-15 17:43:29,782 - modelscope - WARNING - No preprocessor key ('ddcolor', 'image-colorization') found in PREPROCESSOR_MAP, skip building preprocessor.
2024-03-15 17:43:29,785 - modelscope - INFO - load model done
I tried to install the package as README says. But I keep running into this error.
pip install "modelscope[cv]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
Building wheel for torch-scatter (setup.py) ... error
error: subprocess-exited-with-error
× python setup.py bdist_wheel did not run successfully.
│ exit code: 1
╰─> [56 lines of output]
running bdist_wheel
running build
running build_py
creating build
creating build/lib.linux-x86_64-cpython-38
creating build/lib.linux-x86_64-cpython-38/torch_scatter
copying torch_scatter/__init__.py -> build/lib.linux-x86_64-cpython-38/torch_scatter
copying torch_scatter/scatter.py -> build/lib.linux-x86_64-cpython-38/torch_scatter
copying torch_scatter/segment_coo.py -> build/lib.linux-x86_64-cpython-38/torch_scatter
copying torch_scatter/segment_csr.py -> build/lib.linux-x86_64-cpython-38/torch_scatter
copying torch_scatter/utils.py -> build/lib.linux-x86_64-cpython-38/torch_scatter
copying torch_scatter/placeholder.py -> build/lib.linux-x86_64-cpython-38/torch_scatter
copying torch_scatter/testing.py -> build/lib.linux-x86_64-cpython-38/torch_scatter
creating build/lib.linux-x86_64-cpython-38/torch_scatter/composite
copying torch_scatter/composite/__init__.py -> build/lib.linux-x86_64-cpython-38/torch_scatter/composite
copying torch_scatter/composite/softmax.py -> build/lib.linux-x86_64-cpython-38/torch_scatter/composite
copying torch_scatter/composite/logsumexp.py -> build/lib.linux-x86_64-cpython-38/torch_scatter/composite
copying torch_scatter/composite/std.py -> build/lib.linux-x86_64-cpython-38/torch_scatter/composite
running egg_info
writing torch_scatter.egg-info/PKG-INFO
writing dependency_links to torch_scatter.egg-info/dependency_links.txt
writing requirements to torch_scatter.egg-info/requires.txt
writing top-level names to torch_scatter.egg-info/top_level.txt
reading manifest file 'torch_scatter.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
warning: no previously-included files matching '*' found under directory 'test'
adding license file 'LICENSE'
writing manifest file 'torch_scatter.egg-info/SOURCES.txt'
running build_ext
building 'torch_scatter._scatter_cpu' extension
creating build/temp.linux-x86_64-cpython-38
creating build/temp.linux-x86_64-cpython-38/csrc
creating build/temp.linux-x86_64-cpython-38/csrc/cpu
gcc -pthread -B /opt/anaconda3/envs/ddcolor/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DWITH_PYTHON -Icsrc -I/opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include -I/opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -I/opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/TH -I/opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/THC -I/opt/anaconda3/envs/ddcolor/include/python3.8 -c csrc/cpu/scatter_cpu.cpp -o build/temp.linux-x86_64-cpython-38/csrc/cpu/scatter_cpu.o -O3 -Wno-sign-compare -DAT_PARALLEL_OPENMP -fopenmp -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_scatter_cpu -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command-line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
gcc -pthread -B /opt/anaconda3/envs/ddcolor/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DWITH_PYTHON -Icsrc -I/opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include -I/opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -I/opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/TH -I/opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/THC -I/opt/anaconda3/envs/ddcolor/include/python3.8 -c csrc/scatter.cpp -o build/temp.linux-x86_64-cpython-38/csrc/scatter.o -O3 -Wno-sign-compare -DAT_PARALLEL_OPENMP -fopenmp -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -DTORCH_EXTENSION_NAME=_scatter_cpu -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command-line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
csrc/scatter.cpp: In static member function ‘static torch::autograd::variable_list ScatterMean::forward(torch::autograd::AutogradContext*, torch::autograd::Variable, torch::autograd::Variable, int64_t, c10::optional<at::Tensor>, c10::optional<long int>)’:
csrc/scatter.cpp:141:15: error: no matching function for call to ‘at::Tensor::div_(at::Tensor&, const char [6])’
141 | out.div_(count, "floor");
| ~~~~~~~~^~~~~~~~~~~~~~~~
In file included from /opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/ATen/Tensor.h:3,
from /opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/ATen/Context.h:4,
from /opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/ATen/ATen.h:9,
from /opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/torch/script.h:3,
from csrc/scatter.cpp:5:
/opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/ATen/core/TensorBody.h:676:12: note: candidate: ‘at::Tensor& at::Tensor::div_(const at::Tensor&) const’
676 | Tensor & div_(const Tensor & other) const;
| ^~~~
/opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/ATen/core/TensorBody.h:676:12: note: candidate expects 1 argument, 2 provided
/opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/ATen/core/TensorBody.h:678:12: note: candidate: ‘at::Tensor& at::Tensor::div_(c10::Scalar) const’
678 | Tensor & div_(Scalar other) const;
| ^~~~
/opt/anaconda3/envs/ddcolor/lib/python3.8/site-packages/torch/include/ATen/core/TensorBody.h:678:12: note: candidate expects 1 argument, 2 provided
error: command '/usr/bin/gcc' failed with exit code 1
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed building wheel for torch-scatter
Running setup.py clean for torch-scatter
Building wheel for utils (setup.py) ... done
Created wheel for utils: filename=utils-1.0.2-py2.py3-none-any.whl size=13905 sha256=559e4b50d2eb4c91263f8880f054e721eeda25f962e864fd27dc60db83cb2d0a
Stored in directory: /home/c4fun/.cache/pip/wheels/45/68/b5/83c1bab8f5f597186752fcbafaf03e9e2f41a5d03604811e02
Building wheel for aliyun-python-sdk-core (setup.py) ... done
Created wheel for aliyun-python-sdk-core: filename=aliyun_python_sdk_core-2.14.0-py3-none-any.whl size=535290 sha256=c7097f4124d623742976ee1ebd7723709c49728d8991e456ea1f056394d453bb
Stored in directory: /home/c4fun/.cache/pip/wheels/89/2c/1d/580922a0f499547b9ae03217fb31dbbde6dbe784c36d511ad4
Building wheel for crcmod (setup.py) ... done
Created wheel for crcmod: filename=crcmod-1.7-cp38-cp38-linux_x86_64.whl size=30969 sha256=746468d6d24dffc164325eb8a403b578285f9a253bef9fa6f6a44d29851a6958
Stored in directory: /home/c4fun/.cache/pip/wheels/ee/bf/82/ac509f3b383e310a168c1da020cbc62d98c03a6c7c74babc63
Building wheel for iopath (setup.py) ... done
Created wheel for iopath: filename=iopath-0.1.10-py3-none-any.whl size=31530 sha256=d6643c6f3bdbd547e0680c114e408980c771c67a23e63ee8e60afc96508537f4
Stored in directory: /home/c4fun/.cache/pip/wheels/c8/ed/fb/2923ab44724b97e6b8b2cdc98222d5a08fdd65137a787305a0
Building wheel for future (setup.py) ... done
Created wheel for future: filename=future-0.18.3-py3-none-any.whl size=492024 sha256=a906ee7e8be5d9f9ccff1a96d34d76b152d1254d8e31320036ac3d5f00fd75cf
Stored in directory: /home/c4fun/.cache/pip/wheels/70/bd/fa/9f18baf78773526a3f6c9d46f27e09ffd7084a2e2f92825b3b
Building wheel for fire (setup.py) ... done
Created wheel for fire: filename=fire-0.5.0-py2.py3-none-any.whl size=116934 sha256=cb19389f940afd29757278573db0852ba5c07dd99244ebf223c4c798c68231aa
Stored in directory: /home/c4fun/.cache/pip/wheels/82/71/1b/c4c3a0d1c95fe96e69a55dacb72c5fc657b38985f15faa98fd
Successfully built fairscale ffmpeg moviepy trimesh chumpy easydict easyrobust fvcore lap ml-collections antlr4-python3-runtime oss2 utils aliyun-python-sdk-core crcmod iopath future fire
Failed to build torch-scatter
ERROR: Could not build wheels for torch-scatter, which is required to install pyproject.toml-based projects
Hi, I find that, for some gray image with very high contrast, processing it by decreasing contrast can lead to better results. Perhaps the reason is that it aligns more closely with the distribution of the training data.
I wonder if there is any general algorithm or code that can process any given grayscale image, taking into account statistical properties such as color temperature and hue? Thanks a lot!
Any plan to release small pretrained models?
是否能实现Docker部署
Your work is excellent, and I am very interested in it. I'm a beginner and would like to know how to run this code in a Windows environment. When I enter the command, it tells me that basicSR does not exist. Thank you for informing me.
Hello
What is minimum GPU memory value required to run the training?
Hello, thanks for your excellent work!
I want to finetune the given model with my custom dataset, but I don't know where to find the pretrained network_g. Can I finetune the model? Looking forward to your advice.
如何在他们提供的模型,比如ddcolor_modelscope.pth上再次进行训练
The paper is great, I liked it a lot. Could you tell an approximate date for code realease so that I can start experimenting too? Thanks.
How to train by google colab?
Thanks for your great work, results on images even better than deoldify.
I've converted the models to onnx for more simple installation...
Mentioned in the paper:”These color embeddings are initialized to zero during the training phase and used as color queries in the first CDB” , but I can't find the code in the code that initializes to zero in question. Is the initialization to zero mentioned in the paper really zero? Looking forward to your answers.
The FID obtained from testing ImageNet using the pretrained weights provided by you is approximately 17.96.Is there any mistake?
Hello, thanks for your excellent work.
I encountered some problems during training, the code error is as follows:
[2024-07-24 11:56:18,281] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: -11) local_rank: 0 (pid: 14366) of binary:
...
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
basicsr/train.py FAILED
How can I fix it?
Hello congratulations for this work, it's really incredible, is there a way to fix the color instability in the video colorization for objects that move such as cars and people walking? Are there any modifications to be made? Where to train the model with specific modifications? Thank you for your reply
When i run bash scripts/train.sh get error
how can i solve it?
thanks
self._store = TCPStore( # type: ignore[call-arg] RuntimeError: unmatched '}' in format string
Thank you to share tiny model.
When I want to train this model, can you share train method?
When I turn a black-and-white video into a colored one, the video flickers. Sometimes, there is a big difference in color between adjacent frames, which causes the video to flicker. Is there any way to make the video more stable?
Sorry to bother. I'm trying to train DDColor on my own dataset. Is there any training scripts? By the way, how to prepare and organize my dataset?
执行result = img_colorization('https://modelscope.oss-cn-beijing.aliyuncs.com/test/images/audrey_hepburn.jpg')
会报错,内存又够
LICENSE
I get the following errors when i try to run the training script:
/usr/local/lib/python3.9/site-packages/torch/distributed/launch.py:183: FutureWarning: The module torch.distributed.launch is deprecated
and will be removed in future. Use torchrun.
Note that --use-env is set by default in torchrun.
If your script expects --local-rank
argument to be set, please
change it to read from os.environ['LOCAL_RANK']
instead. See
https://pytorch.org/docs/stable/distributed.html#launch-utility for
further instructions
Blogger hello, would like to ask a question, when I run the train.py script, encountered FileNotFoundError: [Errno 2] No such file or directory: 'data_list/imagenet.txt' this problem. I have imagenet.txt in the data_list file, but it keeps saying it can't find it. And this imagenet.txt is generated when you run data_list/get_meta_file.py (I'm afraid I got this wrong)
DDColor has impressive performance to colorize images. We offer a demo page for trying DDColor, supporting both Chinese and English.
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