wcarle/stable-diffusion-videos-openjourney 🔢📝❓ → 🖼️
About
Generate videos by interpolating the latent space of Stable Diffusion using the Openjourney Model
Example Output
Output
Performance Metrics
465.41s
Prediction Time
791.33s
Total Time
All Input Parameters
{
"fps": 15,
"seeds": "42 | 1337",
"prompts": "full body cyborg full-length portrait detailed face symmetric steampunk cyberpunk cyborg intricate detailed to scale hyperrealistic cinematic lighting digital art concept art mdjrny-v4 style | full body cyborg full-length portrait detailed face symmetric steampunk cyberpunk cyborg intricate detailed to scale hyperrealistic cinematic lighting digital art concept art mdjrny-v4 style",
"num_steps": 100,
"scheduler": "klms",
"guidance_scale": 7.5,
"num_inference_steps": 50
}
Input Parameters
- fps
- Frame rate for the video.
- seeds
- Random seed, separated with '|' to use different seeds for each of the prompt provided above. Leave blank to randomize the seed.
- prompts
- Input prompts, separate each prompt with '|'.
- num_steps
- Steps for generating the interpolation video. Recommended to set to 3 or 5 for testing, then up it to 60-200 for better results.
- scheduler
- Choose the scheduler
- guidance_scale
- Scale for classifier-free guidance
- num_inference_steps
- Number of denoising steps for each image generated from the prompt
Output Schema
Output
Example Execution Logs
Setting Random seeds. Seeds used for prompts are: full body cyborg full-length portrait detailed face symmetric steampunk cyberpunk cyborg intricate detailed to scale hyperrealistic cinematic lighting digital art concept art mdjrny-v4 style: 42 full body cyborg full-length portrait detailed face symmetric steampunk cyberpunk cyborg intricate detailed to scale hyperrealistic cinematic lighting digital art concept art mdjrny-v4 style: 1337 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:01<01:19, 1.63s/it] 6%|▌ | 3/50 [00:01<00:22, 2.08it/s] 10%|█ | 5/50 [00:01<00:12, 3.56it/s] 14%|█▍ | 7/50 [00:02<00:08, 5.08it/s] 18%|█▊ | 9/50 [00:02<00:06, 6.49it/s] 22%|██▏ | 11/50 [00:02<00:05, 7.65it/s] 26%|██▌ | 13/50 [00:02<00:04, 8.59it/s] 30%|███ | 15/50 [00:02<00:03, 9.42it/s] 34%|███▍ | 17/50 [00:02<00:03, 10.05it/s] 38%|███▊ | 19/50 [00:03<00:02, 10.58it/s] 42%|████▏ | 21/50 [00:03<00:02, 11.13it/s] 46%|████▌ | 23/50 [00:03<00:02, 11.10it/s] 50%|█████ | 25/50 [00:03<00:02, 10.87it/s] 54%|█████▍ | 27/50 [00:03<00:02, 11.03it/s] 58%|█████▊ | 29/50 [00:04<00:01, 10.80it/s] 62%|██████▏ | 31/50 [00:04<00:01, 11.04it/s] 66%|██████▌ | 33/50 [00:04<00:01, 11.54it/s] 70%|███████ | 35/50 [00:04<00:01, 11.84it/s] 74%|███████▍ | 37/50 [00:04<00:01, 11.89it/s] 78%|███████▊ | 39/50 [00:04<00:00, 12.03it/s] 82%|████████▏ | 41/50 [00:05<00:00, 11.92it/s] 86%|████████▌ | 43/50 [00:05<00:00, 11.61it/s] 90%|█████████ | 45/50 [00:05<00:00, 11.55it/s] 94%|█████████▍| 47/50 [00:05<00:00, 12.02it/s] 98%|█████████▊| 49/50 [00:05<00:00, 11.80it/s] 100%|██████████| 50/50 [00:05<00:00, 8.60it/s] 0%| | 0/50 [00:00<?, ?it/s] 4%|▍ | 2/50 [00:00<00:04, 11.83it/s] 8%|▊ | 4/50 [00:00<00:03, 12.78it/s] 12%|█▏ | 6/50 [00:00<00:03, 12.70it/s] 16%|█▌ | 8/50 [00:00<00:03, 12.55it/s] 20%|██ | 10/50 [00:00<00:03, 12.42it/s] 24%|██▍ | 12/50 [00:00<00:03, 12.14it/s] 28%|██▊ | 14/50 [00:01<00:02, 12.28it/s] 32%|███▏ | 16/50 [00:01<00:02, 12.30it/s] 36%|███▌ | 18/50 [00:01<00:02, 11.79it/s] 40%|████ | 20/50 [00:01<00:02, 11.43it/s] 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Version Details
- Version ID
bd5fd4290fc2ab4b6931c90aee17581a62047470422737e035f34badb8af4132- Version Created
- April 2, 2023