camenduru/dynami-crafter 🔢📝🖼️ → 🖼️
About
DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors

Example Output
Output
Performance Metrics
34.17s
Prediction Time
185.39s
Total Time
All Input Parameters
{ "i2v_eta": 1, "i2v_seed": 123, "i2v_steps": 50, "i2v_motion": 3, "i2v_cfg_scale": 7.5, "i2v_input_text": "boy walking on the street", "i2v_input_image": "https://replicate.delivery/pbxt/K1vHFesvAE0TPLLLY5J5KFFWBVRSh5Akzy6E5oPHvOqpDDGF/boy.webp" }
Input Parameters
- i2v_eta
- ETA
- i2v_seed
- Random Seed
- i2v_steps
- Sampling steps
- i2v_motion
- Motion magnitude
- i2v_cfg_scale
- CFG Scale
- i2v_input_text
- i2v_input_image (required)
- Input image
Output Schema
Output
Example Execution Logs
Seed set to 123 start: boy walking on the street 2023-12-11 12:18:41 /usr/local/lib/python3.10/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True). warnings.warn( /usr/local/lib/python3.10/site-packages/torch/nn/modules/conv.py:459: UserWarning: Applied workaround for CuDNN issue, install nvrtc.so (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:80.) return F.conv2d(input, weight, bias, self.stride,
Version Details
- Version ID
17daec0f8d078e021ba8997118643d0a455d8385f92c44d262e5ce8c259d0575
- Version Created
- December 11, 2023