Video-to-Video
Diffusers
English
Chinese
video-editing
streaming
quantization
int8
text-stream-stripping
Instructions to use kylinfires/Joy-face_change_optimized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kylinfires/Joy-face_change_optimized with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kylinfires/Joy-face_change_optimized", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download training/scripts/evaluation/openvebench.sh from kylinfires/Joy-face_change_optimized: direct link, hf CLI and curl.
- Browser
- Download file 3 kB
-
https://huggingface.co/kylinfires/Joy-face_change_optimized/resolve/main/training/scripts/evaluation/openvebench.sh
- Command line
-
hf download hf://kylinfires/Joy-face_change_optimized/training/scripts/evaluation/openvebench.sh
-
curl -L -o openvebench.sh https://huggingface.co/kylinfires/Joy-face_change_optimized/resolve/main/training/scripts/evaluation/openvebench.sh
3 kB
| set -euo pipefail | |
| ROOT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")/../.." && pwd)" | |
| cd "$ROOT_DIR" | |
| CONFIG="${1:-configs/stage2_distillation.py}" | |
| CKPT="${2:-${JOYAI_CHECKPOINT:-}}" | |
| : "${CKPT:?Pass a checkpoint as the second argument or set JOYAI_CHECKPOINT.}" | |
| DATASET_ROOT="${DATASET_ROOT:-data/OpenVE-Bench}" | |
| CSV_PATH="${CSV_PATH:-${DATASET_ROOT}/benchmark_videos.csv}" | |
| TASK_TYPES="${TASK_TYPES:-global_style,background_change,local_change,local_remove,local_add}" | |
| SAVE="${SAVE:-outputs_eval/openvebench}" | |
| NODE_RANK="${NODE_RANK:-0}" | |
| NEG_PROMPT="An abstract, computer-generated scene with distorted and blurry visuals. A deformed, disfigured figure without specific features, depicted as an illustration. The background is a collage of grainy textures and striped patterns, lacking clear visual content. The figure moves minimally with weak dynamics and a stuttering effect, displaying distorted and erratic motions. The style incorporates extremely high contrast and extremely high sharpness, combined with low-quality imagery, grainy effects, and includes logos and text elements. The camera employs disjointed and stuttering movements, inconsistent framing, and unstructured composition." | |
| EXTRA_ARGS=() | |
| if [[ "${USE_RELATIVE_ROPE:-True}" == "True" ]]; then | |
| EXTRA_ARGS+=(--use-relative-rope) | |
| fi | |
| if [[ "${STORE_CLEAN_ONLY_SELF:-}" == "True" ]]; then | |
| EXTRA_ARGS+=(--store-clean-only-self) | |
| elif [[ "${STORE_CLEAN_ONLY_SELF:-}" == "False" ]]; then | |
| EXTRA_ARGS+=(--no-store-clean-only-self) | |
| fi | |
| if [[ "${USE_PE:-False}" == "True" ]]; then | |
| EXTRA_ARGS+=(--pe-csv-path "${PE_CSV_PATH:-${DATASET_ROOT}/pe_benchmark_videos.csv}") | |
| fi | |
| if [[ -n "${INFERENCE_STEP:-}" ]]; then | |
| EXTRA_ARGS+=(--num-inference-steps "$INFERENCE_STEP") | |
| fi | |
| if [[ -n "${CFG:-}" ]]; then | |
| EXTRA_ARGS+=(--guidance-scale "$CFG") | |
| fi | |
| export PYTHONPATH="$ROOT_DIR${PYTHONPATH:+:$PYTHONPATH}" | |
| torchrun \ | |
| --nnodes "${NNODES:-1}" \ | |
| --nproc_per_node "${GPUS_PER_NODE:-8}" \ | |
| --node_rank "$NODE_RANK" \ | |
| --master_addr "${MASTER_ADDR:-127.0.0.1}" \ | |
| --master_port "${MASTER_PORT:-6000}" \ | |
| --module evaluation.benchmark.infer_openvebench_joyomni \ | |
| --config "$CONFIG" \ | |
| --ckpt-path "$CKPT" \ | |
| --save-path "$SAVE" \ | |
| --dataset-root "$DATASET_ROOT" \ | |
| --csv-path "$CSV_PATH" \ | |
| --task-types "$TASK_TYPES" \ | |
| --source-guidance-scale "${SRC_CFG:-1.0}" \ | |
| --neg-prompt "$NEG_PROMPT" \ | |
| --resolution "${RESOLUTION:-720}" \ | |
| --max-temporal-ids "${MAX_TEMPORAL_IDS:-8}" \ | |
| --seed 42 \ | |
| "${EXTRA_ARGS[@]}" "${@:3}" | |
| if [[ "${RUN_EVAL:-False}" == "True" && "$NODE_RANK" == "0" ]]; then | |
| : "${GEMINI_API_KEY:?Set GEMINI_API_KEY to run evaluation.}" | |
| python evaluation/OpenVE-Bench/eval_openve_gemini.py \ | |
| --video_paths "$SAVE" \ | |
| --dataset-root "$DATASET_ROOT" \ | |
| --csv-path "$CSV_PATH" \ | |
| --task-types "$TASK_TYPES" \ | |
| --model_id "${MODEL_ID:-Gemini-2.5-pro}" \ | |
| --max-workers "${MAX_WORKERS:-32}" | |
| fi | |