Create app.py

app.py

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+import gradio as gr
+import torch
+import os
+import uuid
+from diffusers import AnimateDiffPipeline, EulerDiscreteScheduler
+from diffusers.utils import export_to_video
+from huggingface_hub import hf_hub_download
+from safetensors.torch import load_file
+
+# Constants
+bases = {
+    "Cartoon": "frankjoshua/toonyou_beta6",
+    "Realistic": "emilianJR/epiCRealism",
+    "3d": "Lykon/DreamShaper",
+    "Anime": "Yntec/mistoonAnime2"
+}
+step_loaded = None
+base_loaded = "Realistic"
+motion_loaded = None
+
+# Thiết lập thiết bị CPU và kiểu dữ liệu
+device = "cpu"
+dtype = torch.float32  # Sử dụng float32 thay vì float16 cho CPU
+
+# Khởi tạo pipeline
+pipe = AnimateDiffPipeline.from_pretrained(bases[base_loaded], torch_dtype=dtype).to(device)
+pipe.scheduler = EulerDiscreteScheduler.from_config(
+    pipe.scheduler.config, timestep_spacing="trailing", beta_schedule="linear"
+)
+# Tắt safety checker để tăng tốc
+pipe.safety_checker = None
+
+# Hàm tạo video
+def generate_image(prompt, base="Realistic", motion="", step=1, progress=gr.Progress()):
+    global step_loaded, base_loaded, motion_loaded
+    step = int(step)
+    print(f"Generating video with prompt: {prompt}, base: {base}, steps: {step}")
+
+    # Tải checkpoint AnimateDiff-Lightning
+    if step_loaded != step:
+        repo = "ByteDance/AnimateDiff-Lightning"
+        ckpt = f"animatediff_lightning_{step}step_diffusers.safetensors"
+        pipe.unet.load_state_dict(load_file(hf_hub_download(repo, ckpt), device=device), strict=False)
+        step_loaded = step
+
+    # Tải mô hình cơ sở
+    if base_loaded != base:
+        pipe.unet.load_state_dict(
+            torch.load(hf_hub_download(bases[base], "unet/diffusion_pytorch_model.bin"), map_location=device),
+            strict=False
+        )
+        base_loaded = base
+
+    # Tải motion LoRA (tùy chọn)
+    if motion_loaded != motion:
+        pipe.unload_lora_weights()
+        if motion != "":
+            pipe.load_lora_weights(motion, adapter_name="motion")
+            pipe.set_adapters(["motion"], [0.7])
+        motion_loaded = motion
+
+    progress((0, step))
+    def progress_callback(i, t, z):
+        progress((i + 1, step))
+
+    # Tối ưu hóa suy luận
+    with torch.no_grad():  # Tắt gradient để tiết kiệm bộ nhớ
+        output = pipe(
+            prompt=prompt,
+            guidance_scale=1.2,
+            num_inference_steps=step,
+            callback=progress_callback,
+            callback_steps=1
+        )
+
+    # Xuất video
+    name = str(uuid.uuid4()).replace("-", "")
+    path = f"/tmp/{name}.mp4"
+    export_to_video(output.frames[0], path, fps=10)
+    return path
+
+# Giao diện Gradio
+css = """
+    body {font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; background-color: #f4f4f9; color: #333;}
+    h1 {color: #333; text-align: center; margin-bottom: 20px;}
+    .gradio-container {max-width: 800px; margin: auto; padding: 20px; background: #fff; box-shadow: 0px 0px 20px rgba(0,0,0,0.1); border-radius: 10px;}
+    .gr-input {margin-bottom: 15px;}
+    .gr-button {width: 100%; background-color: #4CAF50; color: white; border: none; padding: 10px 20px; text-align: center; text-decoration: none; display: inline-block; font-size: 16px; border-radius: 5px; cursor: pointer; transition: background-color 0.3s;}
+    .gr-button:hover {background-color: #45a049;}
+    .gr-video {margin-top: 20px;}
+    .gr-examples {margin-top: 30px;}
+    .gr-examples .gr-example {display: inline-block; width: 100%; text-align: center; padding: 10px; background: #eaeaea; border-radius: 5px; margin-bottom: 10px;}
+    .container {display: flex; flex-wrap: wrap;}
+    .inputs, .output {padding: 20px;}
+    .inputs {flex: 1; min-width: 300px;}
+    .output {flex: 1; min-width: 300px;}
+    @media (max-width: 768px) {
+        .container {flex-direction: column-reverse;}
+    }
+    .svelte-1ybb3u7, .svelte-1clup3e {display: none !important;}
+"""
+
+with gr.Blocks(css=css) as demo:
+    gr.HTML("<h1>Instant⚡ Text to Video</h1>")
+    with gr.Row(elem_id="container"):
+        with gr.Column(elem_id="inputs"):
+            prompt = gr.Textbox(label="Prompt", placeholder="Enter text to generate video...", elem_id="gr-input")
+            select_base = gr.Dropdown(
+                label="Base model",
+                choices=["Cartoon", "Realistic", "3d", "Anime"],
+                value=base_loaded,
+                interactive=True,
+                elem_id="gr-input"
+            )
+            select_motion = gr.Dropdown(
+                label="Motion",
+                choices=[
+                    ("Default", ""),
+                    ("Zoom in", "guoyww/animatediff-motion-lora-zoom-in"),
+                    ("Zoom out", "guoyww/animatediff-motion-lora-zoom-out"),
+                    ("Tilt up", "guoyww/animatediff-motion-lora-tilt-up"),
+                    ("Tilt down", "guoyww/animatediff-motion-lora-tilt-down"),
+                    ("Pan left", "guoyww/animatediff-motion-lora-pan-left"),
+                    ("Pan right", "guoyww/animatediff-motion-lora-pan-right"),
+                    ("Roll left", "guoyww/animatediff-motion-lora-rolling-anticockwise"),
+                    ("Roll right", "guoyww/animatediff-motion-lora-rolling-clockwise"),
+                ],
+                value="guoyww/animatediff-motion-lora-zoom-in",
+                interactive=True,
+                elem_id="gr-input"
+            )
+            select_step = gr.Dropdown(
+                label="Inference steps",
+                choices=[("1-Step", 1), ("2-Step", 2), ("4-Step", 4), ("8-Step", 8)],
+                value=1,
+                interactive=True,
+                elem_id="gr-input"
+            )
+            submit = gr.Button("Generate Video", variant="primary", elem_id="gr-button")
+        with gr.Column(elem_id="output"):
+            video = gr.Video(label="AnimateDiff-Lightning", autoplay=True, height=512, width=512, elem_id="gr-video")
+
+    prompt.submit(fn=generate_image, inputs=[prompt, select_base, select_motion, select_step], outputs=video)
+    submit.click(fn=generate_image, inputs=[prompt, select_base, select_motion, select_step], outputs=video)
+
+    gr.Examples(
+        examples=[
+            ["Focus: Eiffel Tower (Animate: Clouds moving)"],
+            ["Focus: Trees In forest (Animate: Lion running)"],
+            ["Focus: Astronaut in Space"],
+            ["Focus: Group of Birds in sky (Animate:  Birds Moving) (Shot From distance)"],
+            ["Focus:  Statue of liberty (Shot from Drone) (Animate: Drone coming toward statue)"],
+            ["Focus: Panda in Forest (Animate: Drinking Tea)"],
+            ["Focus: Kids Playing (Season: Winter)"],
+            ["Focus: Cars in Street (Season: Rain, Daytime) (Shot from Distance) (Movement: Cars running)"]
+        ],
+        fn=generate_image,
+        inputs=[prompt],
+        outputs=video,
+        cache_examples=False,
+        elem_id="gr-examples"
+    )
+
+demo.launch()