Comments (1)
Hello, the random seed is only set once at the beginning of inference, it's designed to reproduce results when you run the script on the same data multiple times. So in your case, if you run inference once, copy out the prediction, and run again, they should be almost the same (due to computational error, they might not be 100% the same).
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Related Issues (20)
- Train a ControlNet plugin instead of full-scale fine-tuning? HOT 1
- how to convert a HF Diffusers saved pipeline to a Stable Diffusion checkpoint? HOT 1
- the test results seem have much noise HOT 4
- Regarding the training convergence HOT 4
- Training on Custom Dataset HOT 1
- the prediction on in-the-wild example is noisy HOT 1
- Is code from the Bas-relief available
- Why set NaN depth values to zero on preprocessing? HOT 1
- Request for vkitti_val.tar and vkitti_vis.tar files HOT 1
- How to Manage the Large Hypersim Dataset for Reproduction? HOT 3
- ask for LCM distillation code HOT 2
- Low-Rank(LoRA) training of Marigold
- Multi-GPU Training HOT 1
- Clarification Needed: Training and Inference Pipeline HOT 4
- Any reason for not using vae.std to generate RGB latent? HOT 1
- do you plan to release better and more accurate models for this original marigold? HOT 1
- The purpose of using v_prediction as the target? HOT 1
- where can I get the "output/marigold_base/checkpoint/latest" HOT 1
- The demo 3D looks ok but not match with the predicted depth image HOT 1
- How to organize the vkitti data HOT 1
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