feat: 初始提交

.gitignore

+.idea
+chenyh

CineDiffusion/.gitignore

+*.DS_Store
+/tests*

CineDiffusion/README.md

+---
+python_version: 3.11.10
+title: CineDiffusion
+emoji: 🎥
+colorFrom: purple
+colorTo: red
+sdk: gradio
+sdk_version: 5.7.0
+app_file: app.py
+pinned: false
+license: apache-2.0
+short_description: Create cinematic images in widescreen aspect ratios.
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

CineDiffusion/app.py

+import gradio as gr
+import numpy as np
+import spaces
+import torch
+from diffusers import DiffusionPipeline
+from numpy.random import PCG64DXSM, Generator, SeedSequence
+from typing import Tuple, Any
+
+dtype: torch.dtype = torch.bfloat16
+device: str = "cuda" if torch.cuda.is_available() else "cpu"
+
+pipe = DiffusionPipeline.from_pretrained("shuttleai/shuttle-3-diffusion", torch_dtype=dtype).to(device)
+trigger_word = "CNSTLL"
+pipe.load_lora_weights("adirik/flux-cinestill")
+# Enable VAE tiling
+pipe.vae.enable_tiling()
+
+# Define cinematic aspect ratios
+ASPECT_RATIOS = {
+    "2.39:1 (Modern Widescreen)": 2.39,
+    "2.76:1 (Ultra Panavision 70)": 2.76,
+    "3.00:1 (Experimental Ultra-wide)": 3.00,
+    "4.00:1 (Polyvision)": 4.00,
+    "2.55:1 (CinemaScope)": 2.55,
+    "2.20:1 (Todd-AO)": 2.20,
+    "2.00:1 (Univisium)": 2.00,
+    "2.35:1 (Anamorphic Scope)": 2.35,
+    "2.59:1 (MGM Camera 65)": 2.59,
+    "1.75:1 (IMAX Digital)": 1.75,
+    "1.43:1 (IMAX 70mm)": 1.43,
+    "2.40:1 (Modern Anamorphic)": 2.40
+}
+MAX_SEED = np.iinfo(np.int64).max
+MIN_WIDTH = 512
+MAX_WIDTH = 3072
+STANDARD_WIDTH = 2048
+STEP_WIDTH = 8
+STYLE_PROMPT = "analog film, high resolution, cinestill 800t, hyperrealistic, widescreen, anamorphic, vignette, bokeh, film grain, dramatic lighting, epic composition, moody, detailed, super wide shot, atmospheric, backlit, soft light,  "
+
+
+def calculate_height(width: int, aspect_ratio: float) -> int:
+    height = int(width / aspect_ratio)
+    return (height // 8) * 8
+
+
+# Pre-calculate height mappings for common widths
+HEIGHT_CACHE = {}
+for ratio_name, ratio in ASPECT_RATIOS.items():
+    HEIGHT_CACHE[ratio_name] = {
+        width: calculate_height(width, ratio)
+        for width in range(MIN_WIDTH, MAX_WIDTH + 1, STEP_WIDTH)
+    }
+
+
+def validate_aspect_ratio(ratio_name: str) -> float | None:
+    return ASPECT_RATIOS.get(ratio_name)
+
+
+# Replace the single rng instance with a function that creates a fresh generator each time
+def get_random_seed() -> int:
+    # Create a new generator with a random seed each time
+    ss = SeedSequence()
+    rng = Generator(PCG64DXSM(ss))
+    return int(rng.integers(0, MAX_SEED))
+
+
+@spaces.GPU()
+def infer(
+        prompt: str,
+        aspect_ratio: str,
+        width: int,
+        seed: Any = 42,  # Change type hint to Any to handle both string and int inputs
+        randomize_seed: bool = False,
+        num_inference_steps: int = 4,
+        progress: Any = gr.Progress(track_tqdm=True)
+) -> Tuple[Any, int]:
+    # Prepend style prompt to user input
+    FULL_PROMPT = f"{STYLE_PROMPT} {prompt}"
+    # print(f"Generating image with prompt: {FULL_PROMPT}")
+
+    if randomize_seed:
+        seed = get_random_seed()
+    else:
+        # Convert seed to int if it's a string
+        seed = int(seed)
+
+    ratio = validate_aspect_ratio(aspect_ratio)
+    if ratio is None:
+        raise ValueError(f"Invalid aspect ratio: {aspect_ratio}")
+
+    generator = torch.Generator().manual_seed(seed)
+    height = HEIGHT_CACHE[aspect_ratio][width]
+    # Calculate megapixel count
+    MEGAPIXEL_COUNT = (width * height) / 1000000
+    print(f"Generating {MEGAPIXEL_COUNT} megapixel image.")
+
+    image = pipe(
+        prompt=FULL_PROMPT,  # Use the combined prompt
+        width=width,
+        height=height,
+        num_inference_steps=num_inference_steps,
+        generator=generator,
+        guidance_scale=3.5,
+        max_sequence_length=256
+    ).images[0]
+    return image, seed
+
+
+examples = [
+    # Rocket Car
+    [
+        "NOT PANORAMIC, NOT MIRRORED. a rocket car going across the bonneville salt flats, the image is blurred to show the immense speed.",
+        # prompt
+        "4.00:1 (Polyvision)",  # aspect_ratio
+        3072,  # width
+        23,  # seed
+        False,  # randomize_seed
+        4,  # num_inference_steps
+    ],
+    # Taxi Driver
+    [
+        "This gripping frame captures a close-up of a man, his face illuminated by the harsh red glow of city lights, evoking a mood of unease and introspection. His expression is intense and unreadable, with a hint of brooding menace. The dark, blurred background suggests a bustling urban night, with neon lights flickering faintly, emphasizing the gritty, isolating atmosphere. The contrast between the man’s rugged features and the vibrant red lighting highlights the tension and internal conflict likely central to the scene, immersing the viewer in the character’s psychological state.",
+        # prompt
+        "2.39:1 (Modern Widescreen)",  # aspect_ratio
+        2048,  # width
+        0,  # seed
+        False,  # randomize_seed
+        4,  # num_inference_steps
+    ],
+    # Leon The Professional
+    [
+        "This tightly framed shot focuses on the reflective lenses of round sun glasses, worn by a figure with weathered skin. The reflections in the glasses reveal a table with cups and hands mid-gesture, suggesting an intense, unseen discussion or ritual taking place. The muted tones and soft lighting enhance the intimate and mysterious mood, drawing attention to the details of the reflections. The perspective feels voyeuristic, as if glimpsing a private moment through the character’s point of view. This evocative close-up emphasizes themes of observation, secrecy, and layered meaning within the narrative.",
+        "2.76:1 (Ultra Panavision 70)",
+        2048,
+        1744078352,
+        False,
+        4,
+    ],
+    # Lawrence of Arabia
+    [
+        "three individuals on camels traversing a vast, sunlit desert. The golden sand stretches endlessly in the foreground, interrupted by the striking presence of dark, rugged mountains in the background, bathed in warm sunlight. The composition emphasizes the isolation and majesty of the desert landscape, with the figures casting long shadows that add depth to the scene. The muted blue sky contrasts beautifully with the earthy tones, creating a balanced and immersive visual. The moment conveys a sense of adventure, introspection, and the timeless allure of the natural world.",
+        "2.20:1 (Todd-AO)",
+        2048,
+        0,
+        False,
+        4,
+    ],
+]
+
+css = """
+body {
+    background-image: url('https://huggingface.co/spaces/takarajordan/CineDiffusion/resolve/main/static/background.webp');
+    background-size: cover;
+    background-position: center;
+    background-repeat: no-repeat;
+    background-attachment: fixed;
+    min-height: 100vh;
+}
+
+gradio-app {
+    background: none !important;
+}
+
+.gradio-container {
+    background-color: white;
+}
+
+.dark .gradio-container {
+    background-color: #121212;
+}
+
+#col-container {
+    margin: 0 auto;
+    max-width: 100%;
+}
+"""
+
+with gr.Blocks(css=css) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown(f"""# CineDiffusion 🎥
+**CineDiffusion** creates cinema-quality widescreen images at up to **4.2 Megapixels** — *4x higher resolution* than typical AI image generators (1MP). Features authentic cinematic aspect ratios for true widescreen results.
+        """)
+
+        with gr.Row():
+            prompt = gr.Text(
+                label="Prompt",
+                show_label=False,
+                placeholder="Enter your prompt",
+                container=True,
+            )
+
+            run_button = gr.Button("Run", scale=0)
+
+        result = gr.Image(
+            label="Result",
+            show_label=False,
+            width="100%",
+            type="pil",
+        )
+
+        with gr.Row():
+            aspect_ratio = gr.Dropdown(
+                label="Aspect Ratio",
+                choices=list(ASPECT_RATIOS.keys()),
+                value="2.39:1 (Modern Widescreen)"
+            )
+
+        with gr.Accordion("Advanced Settings", open=False):
+            seed = gr.Slider(
+                label="Seed",
+                minimum=0,
+                maximum=MAX_SEED,
+                step=1,
+                value=0,
+            )
+
+            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+
+            with gr.Row():
+                width = gr.Slider(
+                    label="Width",
+                    minimum=MIN_WIDTH,
+                    maximum=MAX_WIDTH,
+                    step=STEP_WIDTH,
+                    value=STANDARD_WIDTH,
+                )
+
+            num_inference_steps = gr.Slider(
+                label="Number of inference steps",
+                minimum=1,
+                maximum=50,
+                step=1,
+                value=4,
+            )
+
+        gr.Examples(
+            examples=examples,
+            fn=infer,
+            inputs=[prompt, aspect_ratio, width, seed, randomize_seed, num_inference_steps],
+            outputs=[result, seed],
+            cache_examples=True,
+            cache_mode="lazy"
+        )
+
+    gr.on(
+        triggers=[run_button.click, prompt.submit],
+        fn=infer,
+        inputs=[prompt, aspect_ratio, width, seed, randomize_seed, num_inference_steps],
+        outputs=[result, seed]
+    )
+
+demo.launch(ssr_mode=False, server_name="0.0.0.0", share=True)

CineDiffusion/requirements.txt

+invisible_watermark
+xformers
+sentencepiece
+peft

CineDiffusion/samples/combine.py

+from PIL import Image
+import os
+
+def combine_webp_images():
+    # Get all webp files in current directory
+    webp_files = [f for f in os.listdir('.') if f.endswith('.webp')]
+    
+    if not webp_files:
+        print("No WEBP files found in current directory")
+        return
+    
+    # Open all images
+    images = [Image.open(f) for f in webp_files]
+    
+    # Calculate total height and max width
+    total_height = sum(img.height for img in images)
+    max_width = max(img.width for img in images)
+    
+    # Create new image with combined dimensions
+    combined = Image.new('RGBA', (max_width, total_height))
+    
+    # Paste images one below another
+    y_offset = 0
+    for img in images:
+        combined.paste(img, (0, y_offset))
+        y_offset += img.height
+    
+    # Save combined image
+    combined.save('combined_output.webp', 'WEBP')
+    print(f"Combined {len(webp_files)} images into combined_output.webp")
+
+if __name__ == "__main__":
+    combine_webp_images()

Dockerfile

+FROM image.sourcefind.cn:5000/gpu/admin/base/jupyterlab-pytorch:2.3.1-py3.10-cuda11.8-ubuntu22.04-devel as base
+ARG IMAGE=cinediffusion
+ARG IMAGE_UPPER=CineDiffusion
+ARG BRANCH=gpu
+RUN cd /root && git clone -b $BRANCH http://developer.hpccube.com/codes/chenpangpang/$IMAGE.git
+WORKDIR /root/$IMAGE/$IMAGE_UPPER
+RUN pip install -r requirements.txt
+
+
+#########
+# Prod  #
+#########
+FROM image.sourcefind.cn:5000/gpu/admin/base/jupyterlab-pytorch:2.3.1-py3.10-cuda11.8-ubuntu22.04-devel
+ARG IMAGE=cinediffusion
+ARG IMAGE_UPPER=CineDiffusion
+COPY chenyh/$IMAGE/frpc_linux_amd64_* /opt/conda/lib/python3.10/site-packages/gradio/
+RUN chmod +x /opt/conda/lib/python3.10/dist-packages/gradio/frpc_linux_amd64_*
+COPY chenyh/$IMAGE/ /root/$IMAGE_UPPER/
+COPY --from=base /opt/conda/lib/python3.10/site-packages /opt/conda/lib/python3.10/site-packages
+COPY --from=base /root/$IMAGE/$IMAGE_UPPER /root/$IMAGE_UPPER
+COPY --from=base /root/$IMAGE/启动器.ipynb /root/$IMAGE/start.sh  /root/
+COPY --from=base /root/$IMAGE/assets/  /root/assets/
\ No newline at end of file

hf_down.py

+# pip install huggingface-cli
+import os
+import requests
+import json
+
+os.environ['HF_ENDPOINT'] = 'https://hf-mirror.com'
+
+model_list = [
+        "shuttleai/shuttle-3-diffusion",
+        "adirik/flux-cinestill",
+]
+
+for model_path in model_list:
+    os.system(f"huggingface-cli download --resume-download  {model_path} --local-dir ./{model_path} --local-dir-use-symlinks False")

start.sh

+#!/bin/bash
+
+cd /root/CineDiffusion
+python app.py

启动器.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e5c5a211-2ccd-4341-af10-ac546484b91f",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## 项目介绍\n",
+    "- 原项目地址：https://huggingface.co/spaces/takarajordan/CineDiffusion\n",
+    "- CineDiffusion能够生成高达420万像素的电影级宽屏图像，其分辨率是典型的人工智能图像生成器（100万像素）的4倍。它具备真实的电影级宽高比，能够呈现真正的宽屏效果。\n",
+    "## 运行资源\n",
+    "- 项目在L20显卡，cuda12.2上进行适配\n",
+    "## 使用说明\n",
+    "- 启动和重启 Notebook 点上方工具栏中的「重启并运行所有单元格」。出现如下内容就算成功了：\n",
+    "    - `Running on local URL:  http://0.0.0.0:7860`\n",
+    "    - `Running on public URL: https://xxxxxxxxxxxxxxx.gradio.live`\n",
+    "- 通过以下方式开启页面：\n",
+    "    - 控制台打开「自定义服务」了，访问自定义服务端口号设置为7860\n",
+    "    - 直接打开显示的公开链接`public URL`\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "53a96614-e2d2-4710-a82b-0d5ca9cb9872",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# 启动\n",
+    "!sh start.sh"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "---\n",
+    "**扫码关注公众号，获取更多资讯**<br>\n",
+    "<div align=center>\n",
+    "<img src=\"assets/二维码.jpeg\" width = 20% />\n",
+    "</div>\n"
+   ],
+   "metadata": {
+    "collapsed": false
+   },
+   "id": "2f54158c2967bc25"
+  },
+  {
+   "cell_type": "code",
+   "outputs": [],
+   "source": [],
+   "metadata": {
+    "collapsed": false
+   },
+   "id": "6dc59fbbcf222b6b"
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}