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hao-ai-lab-FastVideo/examples/inference/basic/basic_gamecraft.py
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# SPDX-License-Identifier: Apache-2.0
"""
Basic inference script for HunyuanGameCraft video generation.
HunyuanGameCraft generates game-like videos with camera/action control.
It takes an optional image input and generates video with camera motion
based on simple action commands (forward, left, right, backward, rotations).
Available actions:
- forward (w): Move camera forward
- backward (s): Move camera backward
- left (a): Move camera left (strafe)
- right (d): Move camera right (strafe)
- left_rot: Rotate camera left (pan)
- right_rot: Rotate camera right (pan)
- up_rot: Rotate camera up (tilt)
- down_rot: Rotate camera down (tilt)
T2V vs I2V:
- Default: I2V (uses a default reference image). Set GAMECRAFT_I2V_IMAGE to a
URL or path to use a different image.
- T2V only (no reference image): run with GAMECRAFT_I2V_IMAGE= (empty).
"""
import os
import torch
from fastvideo import VideoGenerator
from fastvideo.models.camera import create_camera_trajectory
# Model configuration (use GAMECRAFT_MODEL_PATH for local weights)
MODEL_PATH = os.environ.get("GAMECRAFT_MODEL_PATH", "FastVideo/HunyuanGameCraft-Diffusers")
# Default prompts for demo
DEFAULT_PROMPTS = {
"village": "A charming medieval village with cobblestone streets, thatched-roof houses, and vibrant flower gardens under a bright blue sky.",
"temple": "A majestic ancient temple stands under a clear blue sky, its grandeur highlighted by towering Doric columns and intricate architectural details.",
"forest": "A lush green forest with tall trees, dappled sunlight filtering through the leaves, and a winding dirt path.",
"beach": "A tropical beach with crystal clear turquoise water, white sand, and palm trees swaying in the breeze.",
}
# I2V: default reference image (URL). Can override with a local path.
DEFAULT_I2V_IMAGE_URL = (
"https://huggingface.co/datasets/huggingface/documentation-images/"
"resolve/main/diffusers/astronaut.jpg"
)
DEFAULT_I2V_PROMPT = (
"An astronaut hatching from an egg, on the surface of the moon, "
"the darkness and depth of space realised in the background."
)
OUTPUT_PATH = "video_samples_gamecraft"
def main():
# Initialize generator
# FastVideo will automatically download weights from HuggingFace
generator = VideoGenerator.from_pretrained(
MODEL_PATH,
num_gpus=1,
use_fsdp_inference=True,
dit_cpu_offload=True,
vae_cpu_offload=True,
text_encoder_cpu_offload=True,
pin_cpu_memory=True,
)
# Video parameters
height = 704
width = 1280
num_frames = 33
action = "forward"
action_speed = 0.2
# Create camera trajectory (Plücker coordinates)
camera_states = create_camera_trajectory(
action=action,
height=height,
width=width,
num_frames=num_frames,
action_speed=action_speed,
dtype=torch.bfloat16,
)
print(f"Camera states shape: {camera_states.shape}")
# I2V vs T2V: unset GAMECRAFT_I2V_IMAGE -> I2V (default image). Set to "" -> T2V.
env_image = os.environ.get("GAMECRAFT_I2V_IMAGE")
if env_image is None:
image_path = DEFAULT_I2V_IMAGE_URL # default: I2V
elif env_image.strip() == "":
image_path = None # T2V
else:
image_path = env_image.strip() # I2V with given URL/path
is_i2v = image_path is not None
prompt = DEFAULT_I2V_PROMPT if is_i2v else DEFAULT_PROMPTS["temple"]
print(f"Mode: {'I2V' if is_i2v else 'T2V'}, prompt: {prompt[:60]}...")
gen_kw = dict(
prompt=prompt,
negative_prompt="",
camera_states=camera_states,
height=height,
width=width,
num_frames=num_frames,
num_inference_steps=50,
guidance_scale=6.0,
seed=42,
fps=24,
output_path=OUTPUT_PATH,
save_video=True,
)
if is_i2v:
gen_kw["image_path"] = image_path
generator.generate_video(**gen_kw)
if __name__ == "__main__":
main()