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@@ -4,23 +4,48 @@ base_model:
4
  - ByteDance-Seed/SeedVR2-3B
5
  - ByteDance-Seed/SeedVR2-7B
6
  ---
 
7
  # ComfyUI-SeedVR2_VideoUpscaler
8
 
9
  [![View Code](https://img.shields.io/badge/πŸ“‚_View_Code-GitHub-181717?style=for-the-badge&logo=github)](https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler)
10
 
11
  Official release of [SeedVR2](https://github.com/ByteDance-Seed/SeedVR) for ComfyUI that enables Upscale Video/Images generation.
12
 
13
- <img src="https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler/raw/main/docs/demo_01.jpg">
14
- <img src="https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler/raw/main/docs/demo_02.jpg">
 
 
15
 
16
- <img src="https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler/raw/main/docs/usage.png">
17
 
18
- ## πŸ†™ Todo
 
 
 
 
 
 
 
 
 
 
19
 
20
- - Fixed unloading the 3B model when the process is finished (sorry about that, I'm trying to find out what's going on)
 
 
 
 
21
 
22
  ## πŸš€ Updates
23
 
 
 
 
 
 
 
 
 
24
  **2025.06.24**
25
 
26
  - πŸš€ Speed up the process until x4 (see new benchmark)
@@ -36,18 +61,18 @@ Official release of [SeedVR2](https://github.com/ByteDance-Seed/SeedVR) for Comf
36
 
37
  - πŸ› οΈ Initial push
38
 
39
- ## Features
40
 
41
  - High-quality Upscaling
42
  - Suitable for any video length once the right settings are found
43
  - Model Will Be Download Automatically from [Models](https://huggingface.co/numz/SeedVR2_comfyUI/tree/main)
44
 
45
- ## Requirements
46
 
47
  - A Huge VRAM capabilities is better, from my test, even the 3B version need a lot of VRAM at least 18GB.
48
  - Last ComfyUI version with python 3.12.9 (may be works with older versions but I haven't test it)
49
 
50
- ## Installation
51
 
52
  1. Clone this repository into your ComfyUI custom nodes directory:
53
 
@@ -64,27 +89,21 @@ load venv and :
64
  pip install -r ComfyUI-SeedVR2_VideoUpscaler/requirements.txt
65
  ```
66
 
67
- install flash_attn or triton if it ask for it
68
 
69
  ```bash
70
  pip install flash_attn
71
  pip install triton
72
  ```
73
 
74
- or from https://github.com/loscrossos/lib_flashattention/releases
75
- and
76
- https://github.com/woct0rdho/triton-windows
77
-
78
- Or use python_embeded :
79
-
80
- ```bash
81
- python_embeded\python.exe -m pip install -r ComfyUI-SeedVR2_VideoUpscaler/requirements.txt
82
- ```
83
 
84
  ```bash
85
  python_embeded\python.exe -m pip install -r flash_attn
86
  ```
87
 
 
 
88
  3. Models
89
 
90
  Will be automtically download into :
@@ -92,71 +111,120 @@ python_embeded\python.exe -m pip install -r flash_attn
92
 
93
  or can be found here ([MODELS](https://huggingface.co/numz/SeedVR2_comfyUI/tree/main))
94
 
95
- ## Usage
96
 
97
  1. In ComfyUI, locate the **SeedVR2 Video Upscaler** node in the node menu.
98
 
99
- <img src="https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler/raw/main/docs/node.png" width="100%">
 
 
100
 
101
- 2. things to know
102
 
103
- **temporal consistency** : at least a batch_size of 5 is required to activate temporal consistency
104
 
105
- 2. Configure the node parameters:
 
 
106
 
107
  - `model`: Select your 3B or 7B model
108
  - `seed`: a seed but it generate another seed from this one
109
- - `new_width`: New desired Width, will keep ration on height
110
- - `cfg_scale`:
111
- - `batch_size`: VERY IMPORTANT!, this model consume a lot of VRAM, All your VRAM, even for the 3B model, so for GPU under 24GB VRAM keep this value Low, good value is "1" without temporal consistency
112
  - `preserve_vram`: for VRAM < 24GB, If true, It will unload unused models during process, longer but works, otherwise probably OOM with
113
 
114
- ## Performance
115
-
116
- **NVIDIA H100 93GB VRAM** (values in parentheses are from the previous benchmark):
117
-
118
- | nb frames | Resolution | Batch Size | Time fp8 (s) | FPS fp8 | Time fp16 (s) | FPS fp16 |
119
- | --------- | ------------------- | ---------- | ---------------- | ----------- | ---------------- | ----------- |
120
- | 3 | 512Γ—768 β†’ 1080Γ—1620 | 1 | 10.18 (58.10) | 0.29 (0.05) | 10.67 (60.13) | 0.28 (0.05) |
121
- | 15 | 512Γ—768 β†’ 1080Γ—1620 | 5 | 26.71 (135.63) | 0.56 (0.11) | 27.75 (144.18) | 0.54 (0.10) |
122
- | 27 | 512Γ—768 β†’ 1080Γ—1620 | 9 | 33.97 (163.22) | 0.79 (0.17) | 35.08 (177.61) | 0.77 (0.15) |
123
- | 39 | 512Γ—768 β†’ 1080Γ—1620 | 13 | 41.01 (189.36) | 0.95 (0.21) | 42.08 (210.11) | 0.93 (0.19) |
124
- | 51 | 512Γ—768 β†’ 1080Γ—1620 | 17 | 48.12 (215.80) | 1.06 (0.24) | 49.44 (242.64) | 1.03 (0.21) |
125
- | 63 | 512Γ—768 β†’ 1080Γ—1620 | 21 | 55.40 (241.79) | 1.14 (0.26) | 56.70 (275.55) | 1.11 (0.23) |
126
- | 75 | 512Γ—768 β†’ 1080Γ—1620 | 25 | 62.60 (267.93) | 1.20 (0.28) | 63.80 (308.51) | 1.18 (0.24) |
127
- | 123 | 512Γ—768 β†’ 1080Γ—1620 | 41 | 91.38 (373.60) | 1.35 (0.33) | 92.90 (440.01) | 1.32 (0.28) |
128
- | 243 | 512Γ—768 β†’ 1080Γ—1620 | 81 | 164.25 (642.20) | 1.48 (0.38) | 166.09 (780.20) | 1.46 (0.31) |
129
- | 363 | 512Γ—768 β†’ 1080Γ—1620 | 121 | 238.18 (913.61) | 1.52 (0.40) | 239.80 (1114.32) | 1.51 (0.33) |
130
- | 453 | 512Γ—768 β†’ 1080Γ—1620 | 151 | 296.52 (1132.01) | 1.53 (0.40) | 298.65 (1384.86) | 1.52 (0.33) |
131
- | 633 | 512Γ—768 β†’ 1080Γ—1620 | 211 | 406.65 (1541.09) | 1.56 (0.41) | 409.44 (1887.62) | 1.55 (0.34) |
132
- | 903 | 512Γ—768 β†’ 1080Γ—1620 | 301 | OOM (OOM) | OOM (OOM) | OOM (OOM) | OOM (OOM) |
133
-
134
- **NVIDIA RTX4090 24GB VRAM** (preserved_vram=off)
135
- | Model | Images | Resolution | Batch Size | Time (seconds) | FPS | Note |
136
- | ------------------------- | ------ | ------------------- | ---------- | -------------- | --- | --- |
137
- | 3B fp8 | 5 | 512x768 β†’ 1080x1620 | 1 | 22.52 | 0.22 | |
138
- | 3B fp16 | 5 | 512x768 β†’ 1080x1620 | 1 | 27.84 | 0.18 | |
139
- | 7B fp8 | 5 | 512x768 β†’ 1080x1620 | 1 | 75.51 | 0.07 | |
140
- | 7B fp16 | 5 | 512x768 β†’ 1080x1620 | 1 | 78.93 | 0.06 | |
141
- | 3B fp8 | 10 | 512x768 β†’ 1080x1620 | 5 | 39.75 | 0.15 | preserve_memory=on|
142
- | 3B fp8 | 20 | 512x768 β†’ 1080x1620 | 1 | 65.40 | 0.31 | |
143
- | 3B fp16 | 20 | 512x768 β†’ 1080x1620 | 1 | 91.12 | 0.22 | |
144
- | 3B fp8 | 20 | 512x768 β†’ 1280x1920 | 1 | 89.10 | 0.22 | |
145
- | 3B fp8 | 20 | 512x768 β†’ 1480x2220 | 1 | 136.08| 0.15 | |
146
- | 3B fp8 | 20 | 512x768 β†’ 1620x2430 | 1 | 191.28 | 0.10 | preserve_memory=on without GPU overload so longer 320sec |
147
-
148
- ## Limitations
 
 
 
 
 
 
 
 
 
 
149
 
150
  - Use a lot of VRAM, it will take all!!
151
  - Processing speed depends on GPU capabilities
152
 
153
- ## Credits
154
 
155
- - Original [SeedVR2](https://github.com/ByteDance-Seed/SeedVR) implementation
156
 
157
- # πŸ“œ License
158
 
159
- - The code in this repository is released under the MIT license as found in the [LICENSE file](LICENSE).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
160
 
 
161
 
 
 
 
 
 
162
 
 
 
 
 
 
 
 
 
4
  - ByteDance-Seed/SeedVR2-3B
5
  - ByteDance-Seed/SeedVR2-7B
6
  ---
7
+
8
  # ComfyUI-SeedVR2_VideoUpscaler
9
 
10
  [![View Code](https://img.shields.io/badge/πŸ“‚_View_Code-GitHub-181717?style=for-the-badge&logo=github)](https://github.com/numz/ComfyUI-SeedVR2_VideoUpscaler)
11
 
12
  Official release of [SeedVR2](https://github.com/ByteDance-Seed/SeedVR) for ComfyUI that enables Upscale Video/Images generation.
13
 
14
+ <img src="docs/demo_01.jpg">
15
+ <img src="docs/demo_02.jpg">
16
+
17
+ <img src="docs/usage.png">
18
 
19
+ ## πŸ“‹ Quick Access
20
 
21
+ - [πŸ†™ Note and futur releases](#-note-and-futur-releases)
22
+ - [πŸš€ Updates](#-updates)
23
+ - [🎯 Features](#-features)
24
+ - [πŸ”§ Requirements](#-requirements)
25
+ - [πŸ“¦ Installation](#-installation)
26
+ - [πŸ“– Usage](#-usage)
27
+ - [πŸ“Š Benchmarks](#-benchmarks)
28
+ - [⚠️ Limitations](#-Limitations)
29
+ - [🀝 Contributing](#-contributing)
30
+ - [πŸ™ Credits](#-credits)
31
+ - [πŸ“„ License](#-license)
32
 
33
+ ## πŸ†™ Note and futur releases
34
+
35
+ - Improve FP8 integration, we are loosing some FP8 advantages during the process.
36
+ - Tile-VAE integration if it works for video, I have test to do or if some dev want help, you are welcome.
37
+ - 7B FP8 model seems to have quality issues, use 7BFP16 instead (If FP8 don't give OOM then FP16 will works) I have to review this.
38
 
39
  ## πŸš€ Updates
40
 
41
+ **2025.06.30**
42
+
43
+ - πŸš€ Speed Up the process and less VRAM used (see new benchmark).
44
+ - πŸ› οΈ Fixed leak memory on 3B models.
45
+ - ❌ Can now interrupt process if needed.
46
+ - βœ… refactored the code for better sharing with the community, feel free to propose pull requests.
47
+ - πŸ› οΈ Removed flash attention dependency
48
+
49
  **2025.06.24**
50
 
51
  - πŸš€ Speed up the process until x4 (see new benchmark)
 
61
 
62
  - πŸ› οΈ Initial push
63
 
64
+ ## 🎯 Features
65
 
66
  - High-quality Upscaling
67
  - Suitable for any video length once the right settings are found
68
  - Model Will Be Download Automatically from [Models](https://huggingface.co/numz/SeedVR2_comfyUI/tree/main)
69
 
70
+ ## πŸ”§ Requirements
71
 
72
  - A Huge VRAM capabilities is better, from my test, even the 3B version need a lot of VRAM at least 18GB.
73
  - Last ComfyUI version with python 3.12.9 (may be works with older versions but I haven't test it)
74
 
75
+ ## πŸ“¦ Installation
76
 
77
  1. Clone this repository into your ComfyUI custom nodes directory:
78
 
 
89
  pip install -r ComfyUI-SeedVR2_VideoUpscaler/requirements.txt
90
  ```
91
 
92
+ install flash_attn/triton, 6% faster on process, not a mandatory.
93
 
94
  ```bash
95
  pip install flash_attn
96
  pip install triton
97
  ```
98
 
99
+ or
 
 
 
 
 
 
 
 
100
 
101
  ```bash
102
  python_embeded\python.exe -m pip install -r flash_attn
103
  ```
104
 
105
+ check here from https://github.com/loscrossos/lib_flashattention/releases and https://github.com/woct0rdho/triton-windows
106
+
107
  3. Models
108
 
109
  Will be automtically download into :
 
111
 
112
  or can be found here ([MODELS](https://huggingface.co/numz/SeedVR2_comfyUI/tree/main))
113
 
114
+ ## πŸ“– Usage
115
 
116
  1. In ComfyUI, locate the **SeedVR2 Video Upscaler** node in the node menu.
117
 
118
+ <img src="docs/node.png" width="100%">
119
+
120
+ 2. ⚠️ **THINGS TO KNOW !!**
121
 
122
+ **temporal consistency** : at least a **batch_size** of 5 is required to activate temporal consistency. SEEDVR2 need at least 5 frames to calculate it. A higher batch_size give better performances/results but need more than 24GB VRAM.
123
 
124
+ **VRAM usage** : The input video resolution impacts VRAM consumption during the process. The larger the input video, the more VRAM will consume during the process. So, if you experience OOMs with a batch_size of at least 5, try reducing the input video resolution until it resolves.
125
 
126
+ Of course, the output resolution also has an impact, so if your hardware doesn't allow it, reduce the output resolution.
127
+
128
+ 3. Configure the node parameters:
129
 
130
  - `model`: Select your 3B or 7B model
131
  - `seed`: a seed but it generate another seed from this one
132
+ - `new_resolution`: New desired short edge in px, will keep ratio on other edge
133
+ - `batch_size`: VERY IMPORTANT!, this model consume a lot of VRAM, All your VRAM, even for the 3B model, so for GPU under 24GB VRAM keep this value Low, good value is "1" without temporal consistency, "5" for temporal consistency, but higher is this value better is the result.
 
134
  - `preserve_vram`: for VRAM < 24GB, If true, It will unload unused models during process, longer but works, otherwise probably OOM with
135
 
136
+ ## πŸ“Š Benchmarks
137
+
138
+ **7B models on NVIDIA H100 93GB VRAM** (values in parentheses are from the previous benchmark):
139
+
140
+ | nb frames | Resolution | Batch Size | execution time fp8 (s) | FPS fp8 | execution time fp16 (s) | FPS fp16 | perf progress since start |
141
+ | --------- | ------------------- | ---------- | ---------------------- | ----------- | ----------------------- | ------------------ | ------------------------- |
142
+ | 15 | 512Γ—768 β†’ 1080Γ—1620 | 5 | 23.75 (26.71) | 0.63 (0.56) | 24.23 (27.75) | 0.61 (0.54) (0.10) | x6.1 |
143
+ | 27 | 512Γ—768 β†’ 1080Γ—1620 | 9 | 27.75 (33.97) | 0.97 (0.79) | 28.48 (35.08) | 0.94 (0.77) (0.15) | x6.2 |
144
+ | 39 | 512Γ—768 β†’ 1080Γ—1620 | 13 | 32.02 (41.01) | 1.21 (0.95) | 32.62 (42.08) | 1.19 (0.93) (0.19) | x6.2 |
145
+ | 51 | 512Γ—768 β†’ 1080Γ—1620 | 17 | 36.39 (48.12) | 1.40 (1.06) | 37.30 (49.44) | 1.36 (1.03) (0.21) | x6.4 |
146
+ | 63 | 512Γ—768 β†’ 1080Γ—1620 | 21 | 40.80 (55.40) | 1.54 (1.14) | 41.32 (56.70) | 1.52 (1.11) (0.23) | x6.6 |
147
+ | 75 | 512Γ—768 β†’ 1080Γ—1620 | 25 | 45.37 (62.60) | 1.65 (1.20) | 45.79 (63.80) | 1.63 (1.18) (0.24) | x6.8 |
148
+ | 123 | 512Γ—768 β†’ 1080Γ—1620 | 41 | 62.44 (91.38) | 1.96 (1.35) | 62.28 (92.90) | 1.97 (1.32) (0.28) | x7.0 |
149
+ | 243 | 512Γ—768 β†’ 1080Γ—1620 | 81 | 106.13 (164.25) | 2.28 (1.48) | 104.68 (166.09) | 2.32 (1.46) (0.31) | x7.4 |
150
+ | 363 | 512Γ—768 β†’ 1080Γ—1620 | 121 | 151.01 (238.18) | 2.40 (1.52) | 148.67 (239.80) | 2.44 (1.51) (0.33) | x7.4 |
151
+ | 453 | 512Γ—768 β†’ 1080Γ—1620 | 151 | 186.98 (296.52) | 2.42 (1.53) | 184.11 (298.65) | 2.46 (1.52) (0.33) | x7.4 |
152
+ | 633 | 512Γ—768 β†’ 1080Γ—1620 | 211 | 253.77 (406.65) | 2.49 (1.56) | 249.43 (409.44) | 2.53 (1.55) (0.34) | x7.4 |
153
+ | 903 | 512Γ—768 β†’ 1080Γ—1620 | 301 | OOM (OOM) | (OOM) | OOM (OOM) | (OOM) (OOM) | |
154
+ | 149 | 854x480 β†’ 1920x1080 | 149 | | | 450.22 | 0.41 | |
155
+
156
+ **3B FP8 models on NVIDIA H100 93GB VRAM** (values in parentheses are from the previous benchmark):
157
+
158
+ | nb frames | Resolution | Batch Size | execution time fp8 (s) | FPS fp8 | execution time fp16 (s) | FPS fp16 |
159
+ | --------- | ------------------- | ---------- | ---------------------- | ------- | ----------------------- | -------- |
160
+ | 149 | 854x480 β†’ 1920x1080 | 149 | 361.22 | 0.41 | | |
161
+
162
+ **NVIDIA RTX4090 24GB VRAM**
163
+
164
+ | Model | nb frames | Resolution | Batch Size | execution time (seconds) | FPS | Note |
165
+ | ------- | --------- | ------------------- | ---------- | ------------------------ | ----------- | ---------------------------------------- |
166
+ | 3B fp8 | 5 | 512x768 β†’ 1080x1620 | 1 | 14.66 (22.52) | 0.34 (0.22) | |
167
+ | 3B fp16 | 5 | 512x768 β†’ 1080x1620 | 1 | 17.02 (27.84) | 0.29 (0.18) | |
168
+ | 7B fp8 | 5 | 512x768 β†’ 1080x1620 | 1 | 46.23 (75.51) | 0.11 (0.07) | preserve_memory=on |
169
+ | 7B fp16 | 5 | 512x768 β†’ 1080x1620 | 1 | 43.58 (78.93) | 0.11 (0.06) | preserve_memory=on |
170
+ | 3B fp8 | 10 | 512x768 β†’ 1080x1620 | 5 | 39.75 | 0.25 | preserve_memory=on |
171
+ | 3B fp8 | 100 | 512x768 β†’ 1080x1620 | 5 | 322.77 | 0.31 | preserve_memory=on |
172
+ | 3B fp8 | 1000 | 512x768 β†’ 1080x1620 | 5 | 3624.08 | 0.28 | preserve_memory=on |
173
+ | 3B fp8 | 20 | 512x768 β†’ 1080x1620 | 1 | 40.71 (65.40) | 0.49 (0.31) | |
174
+ | 3B fp16 | 20 | 512x768 β†’ 1080x1620 | 1 | 44.76 (91.12) | 0.45 (0.22) | |
175
+ | 3B fp8 | 20 | 512x768 β†’ 1280x1920 | 1 | 61.14 (89.10) | 0.33 (0.22) | |
176
+ | 3B fp8 | 20 | 512x768 β†’ 1480x2220 | 1 | 79.66 (136.08) | 0.25 (0.15) | |
177
+ | 3B fp8 | 20 | 512x768 β†’ 1620x2430 | 1 | 125.79 (191.28) | 0.16 (0.10) | preserve_memory=off (preserve_memory=on) |
178
+ | 3B fp8 | 149 | 854x480 β†’ 1920x1080 | 5 | 782.76 | 0.19 | preserve_memory=on |
179
+
180
+ ## ⚠️ Limitations
181
 
182
  - Use a lot of VRAM, it will take all!!
183
  - Processing speed depends on GPU capabilities
184
 
185
+ ## 🀝 Contributing
186
 
187
+ Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.
188
 
189
+ Please make sure to update tests as appropriate.
190
 
191
+ ### How to contribute:
192
+
193
+ 1. Fork the repository
194
+ 2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
195
+ 3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
196
+ 4. Push to the branch (`git push origin feature/AmazingFeature`)
197
+ 5. Open a Pull Request
198
+
199
+ ### Development Setup:
200
+
201
+ 1. Clone the repository
202
+ 2. Install dependencies
203
+ 3. Make your changes
204
+ 4. Test your changes
205
+ 5. Submit a pull request
206
+
207
+ ### Code Style:
208
+
209
+ - Follow the existing code style
210
+ - Add comments for complex logic
211
+ - Update documentation if needed
212
+ - Ensure all tests pass
213
+
214
+ ### Reporting Issues:
215
 
216
+ When reporting issues, please include:
217
 
218
+ - Your system specifications
219
+ - ComfyUI version
220
+ - Python version
221
+ - Error messages
222
+ - Steps to reproduce the issue
223
 
224
+ ## πŸ™ Credits
225
+
226
+ - Original [SeedVR2](https://github.com/ByteDance-Seed/SeedVR) implementation
227
+
228
+ # πŸ“œ License
229
+
230
+ - The code in this repository is released under the MIT license as found in the [LICENSE file](LICENSE).