06.04.2026, 09:33
but in R74, the constants vs.RANGE_FULL (=0) and vs.RANGE_LIMITED (=1) are still defined ? vs
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Deoldify Vapoursynth filter
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06.04.2026, 09:33
but in R74, the constants vs.RANGE_FULL (=0) and vs.RANGE_LIMITED (=1) are still defined ? vs
myrsloik mentionend that one should use the constants,...
Looking in the code: typedef enum VSRange {=> using the constants is fine, Vapoursynth switches the values depending on where the value is set. ![]() And yes, the constants are still there https://github.com/vapoursynth/vapoursyn...t__.py#L14 Cu Selur
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Dev versions are in the 'experimental'-folder of my GoogleDrive, which is linked on the download page.
06.04.2026, 10:38
But this code will work in R74 ?
if vs.core.core_version.release_major < 74:In R72 this code will work, but since I don't have R74 installed, I cannot test it in R74. Dan
I see no reason for it not to work.
![]() (haven't tested )I plan to setup a test R74 with Python 3.12 later today.
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Dev versions are in the 'experimental'-folder of my GoogleDrive, which is linked on the download page.
06.04.2026, 11:43
Code, works fine with R74. (tested)
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Dev versions are in the 'experimental'-folder of my GoogleDrive, which is linked on the download page.
06.04.2026, 16:11
Released new version: v5.6.7
Main changes: Improved connection error handling in ColorMNetDan
06.04.2026, 17:40
are any adjustments to Hybrid needed?
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Dev versions are in the 'experimental'-folder of my GoogleDrive, which is linked on the download page.
06.04.2026, 18:49
No, all the changes are related to API not directly exposed in Hybrid.
I improved the scene detection algorithm and this was necessary to allow the use of DiT models as additional coloring model. The next big change will be the direct support of DiT models in Hybrid, but for such step I need that will be released a DiT model with low hardware requirements. Unfortunately most of the researchers working on Qwen left Alibaba and I don't know if they will start to produce new lightweight models in other companies. Fortunately the high VRAM cost is providing an incentive to many researchers to develop models with lower RAM usage. We'll see... Dan
25.04.2026, 19:32
Hello Selur,
I included in HAVC the new model CMNET2 discussed in this thread ColormnetV2 Project. CMNET2 has solved the main problems that plagued HAVC: color inconsistency and color degradation. CMNET2 is so good at maintaining color consistency that it can even stabilize DDColor without adding additional filters, something I thought was impossible until CMNET2 was developed. The main components introduced in CMNET2: permanent memory and sliding memory window, working together they have made it possible to achieve this incredible result. I attached the RC4 of new HAVC version 5.8.0. Main changes on GUI side are: 1) The Exemplar Models available now are: 0 : CMNET2 (default) -> new model 1 : Deep-Exemplar 2 : Deep-Remaster 3 : ColorMNet -> previously was index=0 2) The presets to control the render method and speed, are: 'Auto' : will be automatically assigned the optimal render size (default) -> NEW 'Fast' : colors are more washed out 'Medium' : colors are a little washed out 'Slow' : colors are a little more vivid 'Slower' : colors are more accurate (usually is very slow) -> NEW I tried to minimize the impact on GUI. I hope that you had time to update Hybrid (my current installed version is 2026.04.24.1 with R74) Thanks, Dan
25.04.2026, 19:52
Hello Dan,
Excellent news! You have done a very good job!!! CMNET2 sounds like a major step forward, especially if it truly solves the long-standing issues of color inconsistency and degradation. The fact that it can stabilize DDColor without additional filters is particularly impressive. Permanent memory combined with the sliding memory window seems like a very smart and powerful approach. Thank you as well for keeping the GUI changes minimal while still adding meaningful improvements. The new presets and the inclusion of CMNET2 as default make a lot of sense. I really appreciate the work and dedication you continue to put into HAVC. Looking forward to seeing this new version integrated and tested further. Best regards, NASS |
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