ckpt

examples/inference/basic/basic_hy15.py

@@ -2,14 +2,14 @@ from fastvideo import VideoGenerator
 import json
 # from fastvideo.configs.sample import SamplingParam
 
-OUTPUT_PATH = "video_samples_hy15_ti2v"
+OUTPUT_PATH = "video_samples_hy15_t2v_distilled"
 def main():
     # FastVideo will automatically use the optimal default arguments for the
     # model.
     # If a local path is provided, FastVideo will make a best effort
     # attempt to identify the optimal arguments.
     generator = VideoGenerator.from_pretrained(
-        "hunyuanvideo-community/HunyuanVideo-1.5-Diffusers-480p_t2v",
+        "hunyuanvideo-community/HunyuanVideo-1.5-Diffusers-480p_i2v_step_distilled",
         # FastVideo will automatically handle distributed setup
         num_gpus=1,
         use_fsdp_inference=False, # set to True if GPU is out of memory
@@ -18,14 +18,26 @@ def main():
         text_encoder_cpu_offload=True,
         pin_cpu_memory=True, # set to false if low CPU RAM or hit obscure "CUDA error: Invalid argument"
         # image_encoder_cpu_offload=False,
-        ti2v_task=True,
+        # init_weights_from_safetensors="/mnt/weka/home/hao.zhang/wei/SFhy1.5_distill_1333_5e-5_2e-6_cfg3.5/checkpoint-500/ema/generator_ema.safetensors"
     )
 
+    # json_path = "/mnt/weka/home/hao.zhang/wei/FastVideo/data/mixkit_i2v_full_720p.json"
+    # with open(json_path, 'r') as f:
+    #     data_list = json.load(f)["data"]
+    
+    # # Now you can index into data_list however you like
+    # # For example: data_list[0], data_list[1:3], etc.
+    # for data in data_list:
+    #     prompt = data["prompt"]
+    #     image_path = data["image_path"]
+    #     generator.generate_video(prompt, output_path=OUTPUT_PATH, save_video=True, image_path=image_path, num_frames=121, fps=24)
+    # return
+
     # prompt = (
     #     "In a brightly lit studio, a photographer wearing a denim jacket focuses intently, capturing shots with a professional camera. Facing him, a model stands gracefully, adjusting her long, flowing hair with delicate movements. The scene is characterized by strong contrasts; the model's soft pink attire and gentle gestures complement the rugged, precise demeanor of the photographer. Positioned against a minimalist backdrop, the pair work seamlessly, with the camera\u2019s lens pointed directly at the model, capturing her elegance. The soft, diffused lighting casts a gentle glow on both subjects, creating an airy and ethereal atmosphere perfect for a high-fashion photo shoot."
     # )
 
-    # video = generator.generate_video(prompt, output_path=OUTPUT_PATH, save_video=True, negative_prompt="", num_frames=81, fps=16, image_path="data/1.png")
+    # video = generator.generate_video(prompt, output_path=OUTPUT_PATH, save_video=True, negative_prompt="", num_frames=121, fps=24, image_path="data/1.png")
     # return
 
     prompt = (
@@ -34,7 +46,7 @@ def main():
         "natural light filtering through the petals. Mid-shot, warm and cheerful tones."
     )
 
-    video = generator.generate_video(prompt, output_path=OUTPUT_PATH, save_video=True, negative_prompt="", num_frames=73, fps=16)
+    video = generator.generate_video(prompt, output_path=OUTPUT_PATH, save_video=True)
 
     prompt2 = (
         "A majestic lion strides across the golden savanna, its powerful frame "
@@ -43,7 +55,7 @@ def main():
         "embodying the raw energy of the wild. Low angle, steady tracking shot, "
         "cinematic.")
 
-    video2 = generator.generate_video(prompt2, output_path=OUTPUT_PATH, save_video=True, negative_prompt="", num_frames=73, fps=16)
+    video2 = generator.generate_video(prompt2, output_path=OUTPUT_PATH, save_video=True)
 
 
 if __name__ == "__main__":