Create app.py

app.py

@@ -0,0 +1,81 @@
+import spaces
+import gradio as gr
+import argparse
+import sys
+import time
+import os
+import random
+from skyreelsinfer import TaskType
+from skyreelsinfer.offload import OffloadConfig
+from skyreelsinfer.skyreels_video_infer import SkyReelsVideoInfer
+from diffusers.utils import export_to_video
+from diffusers.utils import load_image
+
+predictor = None
+task_type = None
+
+def init_predictor():
+    global predictor
+    predictor = SkyReelsVideoInfer(
+        task_type= TaskType.I2V
+        model_id="Skywork/SkyReels-V1-Hunyuan-I2V",
+        quant_model=True,
+        world_size=gpu_num,
+        is_offload=True,
+        offload_config=OffloadConfig(
+            high_cpu_memory=True,
+            parameters_level=True,
+            compiler_transformer=False,
+        )
+    )
+
+@spaces.GPU(duration=90)
+def generate_video(prompt, seed, image=None):
+    global task_type
+    print(f"image:{type(image)}")
+    if seed == -1:
+        random.seed(time.time())
+        seed = int(random.randrange(4294967294))
+    kwargs = {
+        "prompt": prompt,
+        "height": 512,
+        "width": 512,
+        "num_frames": 97,
+        "num_inference_steps": 30,
+        "seed": seed,
+        "guidance_scale": 6.0,
+        "embedded_guidance_scale": 1.0,
+        "negative_prompt": "Aerial view, aerial view, overexposed, low quality, deformation, a poor composition, bad hands, bad teeth, bad eyes, bad limbs, distortion",
+        "cfg_for": False,
+    }
+    assert image is not None, "please input image"
+    kwargs["image"] = load_image(image=image)
+    global predictor
+    output = predictor.inference(kwargs)
+    save_dir = f"./result/{task_type}"
+    os.makedirs(save_dir, exist_ok=True)
+    video_out_file = f"{save_dir}/{prompt[:100].replace('/','')}_{seed}.mp4"
+    print(f"generate video, local path: {video_out_file}")
+    export_to_video(output, video_out_file, fps=24)
+    return video_out_file, kwargs
+
+def create_gradio_interface():
+        with gr.Blocks() as demo:
+            with gr.Row():
+                image = gr.Image(label="Upload Image", type="filepath")
+                prompt = gr.Textbox(label="Input Prompt")
+                seed = gr.Number(label="Random Seed", value=-1)
+            submit_button = gr.Button("Generate Video")
+            output_video = gr.Video(label="Generated Video")
+            output_params = gr.Textbox(label="Output Parameters")
+            submit_button.click(
+                fn=generate_video,
+                inputs=[prompt, seed, image],
+                outputs=[output_video, output_params],
+            )
+    return demo
+
+if __name__ == "__main__":
+    init_predictor()
+    demo = create_gradio_interface()
+    demo.launch()