Create tospacecommit_beta

tospacecommit_beta

@@ -0,0 +1,574 @@
+import gradio as gr
+import torch
+import random
+import numpy as np
+import datetime
+
+# 履歴保存
+from huggingface_hub import HfApi
+from huggingface_hub import login
+from huggingface_hub import Repository
+
+import os
+# HF_TOKEN 環境変数からトークンを明示的に読み込む
+hf_token_value = os.getenv("HF_TOKEN")
+
+if hf_token_value:
+    api = HfApi(token=hf_token_value)
+    print("token ok.")
+else:
+    # トークンが設定されていない場合の警告と代替処理
+    print("HF_TOKEN error")
+    api = HfApi() # トークンなしで初期化
+
+# 画像をアップロードするリポジトリID
+HF_REPO_ID = "cocoat/images"
+
+# Space内で画像を保存するディレクトリ
+SPACE_IMAGE_DIR = "generated_images"
+os.makedirs(SPACE_IMAGE_DIR, exist_ok=True)
+
+# Spaceのリポジトリを初期化
+# Gradio Spaceでは、カレントディレクトリがSpaceのリポジトリのルートになります。
+# HF_SPACE_ID 環境変数には "ユーザー名/スペース名" が入っています。
+space_repo_id = "cocoat/Re.cocoamixXL3"
+repo = None # repoオブジェクトを初期化
+if space_repo_id:
+    try:
+        repo = Repository(local_dir=".")
+        print(f"Successfully initialized Repository object for Space: {space_repo_id}")
+    except Exception as e:
+        print(f"Failed to initialize Repository object for Space ({space_repo_id}): {e}")
+else:
+    print("HF_SPACE_ID environment variable not found. Cannot operate on Space repository.")
+
+# 履歴ファイルを定義
+HISTORY_FILE = "history/generation_history_coamixXL3.txt"
+
+# 履歴をロードする関数
+import os
+import requests
+def load_history():
+    history_data = []
+    hf_raw_file_url = f"https://huggingface.co/datasets/{HF_REPO_ID}/raw/main/{HISTORY_FILE}"
+    headers = {}
+    if hf_token_value:
+        headers["Authorization"] = f"Bearer {hf_token_value}"
+
+    try:
+        response = requests.get(hf_raw_file_url, headers=headers)
+        response.raise_for_status()
+
+        loaded_hub_paths = set() # 重複ロードを防ぐため
+
+        for line in response.text.splitlines():
+            parts = line.strip().split("|||")
+            if len(parts) == 2:
+                image_path_in_repo, caption = parts
+                
+                filename_from_hub_path = os.path.basename(image_path_in_repo)
+                space_local_image_path = os.path.join(SPACE_IMAGE_DIR, filename_from_hub_path)
+                
+                # Space内にファイルが存在するか確認
+                if os.path.exists(space_local_image_path):
+                    # 存在するなら Space のパスを使用
+                    history_data.append((image_path_in_repo, caption, space_local_image_path))
+                    loaded_hub_paths.add(image_path_in_repo)
+                else:
+                    print(f"Warning: Space image not found for Hub path: {image_path_in_repo}. Skipping for display.")
+        print(f"History loaded from Hub and matched with Space images: {len(history_data)} entries.")
+    except requests.exceptions.RequestException as e:
+        print(f"Error loading history from Hub via raw URL: {e}. Starting with empty history.")
+    except Exception as e:
+        print(f"An unexpected error occurred while parsing history: {e}. Starting with empty history.")
+
+    return history_data[:10]
+
+
+# 履歴を初期化時にロード (修正された load_history を使用)
+history = load_history()
+
+
+# 履歴を初期化時にロード
+history = load_history()
+
+from PIL import Image
+from diffusers import (
+    StableDiffusionXLPipeline,
+    EulerAncestralDiscreteScheduler,
+    DPMSolverMultistepScheduler
+)
+from huggingface_hub import hf_hub_download, HfApi
+
+# デバイスと型の設定
+device = "cuda" if torch.cuda.is_available() else "cpu"
+torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
+MAX_SEED = np.iinfo(np.int32).max
+MAX_SIZE = 2048
+
+# モデルファイルのダウンロード
+model_path = hf_hub_download(
+    repo_id="cocoat/cocoamix",
+    filename="recocoamixXL3_coamixXL3.safetensors"
+)
+
+# パイプライン構築
+pipe = StableDiffusionXLPipeline.from_single_file(
+    model_path,
+    torch_dtype=torch_dtype,
+    use_safetensors=True
+).to(device)
+
+# スケジューラ設定
+euler_scheduler = EulerAncestralDiscreteScheduler.from_config(
+    pipe.scheduler.config,
+    use_karras_sigmas=True
+)
+dpm_scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
+pipe.scheduler = euler_scheduler
+
+def upload_image_to_hub(image_pil, prompt_text):
+    # ファイル名を生成（タイムスタンプとプロンプトの一部）
+    timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+    # プロンプトから安全なファイル名の一部を生成
+    # safe_prompt = "".join(c for c in prompt_text if c.isalnum() or c in (' ', '.', '_')).replace(' ', '_')[:30]
+    filename = f"image_{timestamp}.png"
+    filepath = f"temp_{filename}"
+    image_pil.save(filepath)
+
+    # Hubにアップロード
+    try:
+        # リポジトリ内にディレクトリを作成する場合は path_in_repo を使う
+        path_in_repo = f"generated_images/{filename}"
+        upload_info = api.upload_file(
+            path_or_fileobj=filepath,
+            path_in_repo=path_in_repo,
+            repo_id=HF_REPO_ID,
+            repo_type="dataset", # または "space", "model" など、目的のリポジトリタイプ
+            # 通常、画像保存には "dataset" タイプのリポジトリが適しています
+        )
+               # アップロードされたファイルのURLを構築する
+        uploaded_file_url = f"https://huggingface.co/datasets/{HF_REPO_ID}/resolve/main/{path_in_repo}"
+        print(f"Uploaded {filepath} to {uploaded_file_url}")
+        return uploaded_file_url
+    except Exception as e:
+        print(f"Error uploading image to Hub: {e}")
+        return None
+    finally:
+        # 一時ファイルを削除
+        if os.path.exists(filepath):
+            os.remove(filepath)
+            print(f"一時画像ファイル {filepath} を削除しました。")
+
+def make_html_table(caption):
+    formatted_caption = caption.replace("|-|", "\n")
+    rows = formatted_caption.split("\n")
+    html = '<table style="width:100%;border-collapse:collapse;background:#fffaf1;color:#000">'
+    for row in rows:
+        if ": " in row:
+            key, val = row.split(": ", 1)
+            html += (
+#                f'{key}: {val}\n'
+                f'<tr><th style="text-align:left;border:1px solid #ddd;padding:4px;">{key}</th>'
+                f'<td style="border:1px solid #ddd;padding:4px;">{val}</td></tr>'
+            )
+    html += '</table>'
+    return html
+
+def create_dummy_image(width=512, height=512, alpha=0):
+    return Image.new("RGBA", (width, height), (0, 0, 0, alpha))
+
+def update_history_tables_on_select(evt: gr.SelectData):
+    if evt.index is not None and 0 <= evt.index < len(history):
+        selected_caption = history[evt.index][1]
+        return make_html_table(selected_caption)
+    return ""
+
+def update_history():
+    tables_html = "".join(
+        f'<div style="margin-bottom:12px">{make_html_table(item[1])}</div>'
+        for item in history
+    )
+    return tables_html
+
+def infer(prompt, neg, seed, rand, w, h, cfg, steps, scheduler_type,
+          progress=gr.Progress(track_tqdm=True)):
+    if rand:
+        seed = random.randint(0, MAX_SEED)
+    generator = torch.Generator(device=device).manual_seed(seed)
+
+    pipe.scheduler = euler_scheduler if scheduler_type == "Euler Ancestral" else dpm_scheduler
+    pipe.scheduler.set_timesteps(steps)
+
+    def _callback(pipeline, step_idx, timestep, callback_kwargs):
+        progress(step_idx / steps, desc=f"Step {step_idx}/{steps}")
+        return callback_kwargs
+
+    output = pipe(
+        prompt=prompt,
+        negative_prompt=neg or None,
+        guidance_scale=cfg,
+        num_inference_steps=steps,
+        width=w,
+        height=h,
+        generator=generator,
+        callback_on_step_end=_callback
+    )
+    img = output.images[0]
+
+    caption_text = (
+        f"Prompt: {prompt}\n"
+        f"Negative: {neg or 'None'}\n"
+        f"Seed: {seed}\n"
+        f"Size: {w}×{h}\n"
+        f"CFG: {cfg}\n"
+        f"Steps: {steps}\n"
+        f"Scheduler: {scheduler_type}"
+    )
+
+    caption_text_for_history = caption_text.replace("\n", "|-|").strip()
+    
+    # 画像をHubにアップロードし、そのURLを取得
+    uploaded_image_url = upload_image_to_hub(img, prompt)
+
+    # Space内に画像を保存し、Gitリポジリにコミット・プッシュ
+    timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
+    space_image_filename = f"space_image_{timestamp}.png"
+    space_image_filepath = os.path.join(SPACE_IMAGE_DIR, space_image_filename)
+    
+    saved_to_space_git = False
+    try:
+        img.save(space_image_filepath)
+        print(f"Image saved to Space local filesystem: {space_image_filepath}")
+        
+        # SpaceのGitリポジトリにコミット・プッシュ
+        if repo:
+            try:
+                # Git LFS で追跡するように .gitattributes を確認/追加
+                gitattributes_path = os.path.join(SPACE_IMAGE_DIR, ".gitattributes")
+                if not os.path.exists(gitattributes_path):
+                    with open(gitattributes_path, "w") as f:
+                        f.write("*.png filter=lfs diff=lfs merge=lfs -text\n")
+                    repo.git_add(gitattributes_path)
+                    print(f"Added .gitattributes for LFS tracking in {SPACE_IMAGE_DIR}.")
+
+                repo.git_add(space_image_filepath)
+                repo.git_commit(f"Add generated image {space_image_filename}")
+                repo.git_push() # これでHubにプッシュされる
+                print(f"Image {space_image_filename} committed and pushed to Space repository.")
+                saved_to_space_git = True
+            except Exception as e:
+                print(f"Error committing/pushing image to Space repository: {e}")
+        else:
+            print("Space repository object not initialized, skipping Git operations for Space.")
+            
+    except Exception as e:
+        print(f"Error saving image to Space local filesystem: {e}")
+        saved_to_space_git = False # エラー時にはFalseに設定を保証
+    
+    # 履歴を更新
+    global history
+        # Hubへのアップロードが成功し、かつSpaceへのGit保存も成功した場合のみ履歴に追加
+    if uploaded_image_url and saved_to_space_git:
+        path_in_repo_for_history = uploaded_image_url.split(f"huggingface.co/datasets/{HF_REPO_ID}/resolve/main/")[1]
+        history.insert(0, (path_in_repo_for_history, caption_text_for_history, space_image_filepath))
+    else:
+        print(f"Skipping history update due to failed Hub upload ({uploaded_image_url is None}) or Space Git save ({not saved_to_space_git}).")
+
+    history_max_items = 10
+    if len(history) > history_max_items:
+        # Space内の最も古い画像を削除
+        if history[-1][2] and os.path.exists(history[-1][2]): 
+            oldest_space_image_path = history[-1][2] 
+            try:
+                if repo: # repoオブジェクトが初期化されていればGit操作
+                    repo.git_rm(oldest_space_image_path) # Gitからファイルを削除
+                    repo.git_commit(f"Remove oldest image {os.path.basename(oldest_space_image_path)}")
+                    repo.git_push()
+                    print(f"Deleted oldest image from Space repository: {oldest_space_image_path}")
+                else: # repoオブジェクトがない場合はローカルファイルのみ削除
+                    os.remove(oldest_space_image_path) 
+                    print(f"Deleted oldest image from Space local filesystem (no Git): {oldest_space_image_path}")
+            except Exception as e:
+                print(f"Error deleting oldest image from Space (local/Git): {e}")
+        history.pop()
+
+    # 履歴ファイルを更新し、Hubにアップロードする
+    temp_history_filepath = "temp_history.txt"
+    with open(temp_history_filepath, "w", encoding="utf-8") as f:
+        for img_path_in_repo, cap_text, _ in history:
+            f.write(f"{img_path_in_repo}|||{cap_text}\n")
+
+    try:
+        api.upload_file(
+            path_or_fileobj=temp_history_filepath,
+            path_in_repo=HISTORY_FILE,
+            repo_id=HF_REPO_ID,
+            repo_type="dataset",
+        )
+        print(f"History file '{HISTORY_FILE}' updated on Hugging Face Hub.")
+    except Exception as e:
+        print(f"Error updating history file on Hub: {e}")
+    finally:
+        if os.path.exists(temp_history_filepath):
+            os.remove(temp_history_filepath)
+
+    progress(1.0, desc="Done!")
+
+    # ギャラリー表示用のアイテムリストを生成（Hub上のURLを使用）
+    gallery_items = [(item[2], item[1].replace("|-|", "\n")) for item in history]
+    
+    processed_img, processed_gallery_items = process_image(img, gallery_items)
+    
+    latest_caption_table = make_html_table(caption_text)
+    return processed_img, processed_gallery_items, latest_caption_table
+
+import gc
+import torch
+def process_image(img, gallery_items): # Assuming this is part of a function
+    try:
+        gc.collect()        
+        # Clear PyTorch's cache if GPU memory is being used
+        if torch.cuda.is_available():
+            torch.cuda.empty_cache()
+        return img, gallery_items
+
+    except RuntimeError as e:
+        # Catch errors like CUDA Out of Memory
+        error_message = f"error in generate: {e}\n\n"
+        if "CUDA out of memory" in str(e):
+            error_message += "memory error"
+        else:
+            error_message += "other error"
+        print(error_message) # Output to server logs
+        return None, None
+
+# CSS 設定（ダークモード強制防止＋カフェ風テーマ）
+css = """
+@import url('https://fonts.googleapis.com/css2?family=Playpen+Sans+Hebrew:wght@100;200;300;400;500;600;700;800&display=swap');
+body {
+  background-color: #f4e1c1 !important;
+  font-family:'Playpen Sans Hebrew', ‘Georgia’, serif !important;
+  color: #000 !important;
+}
+html, .gradio-container, .dark, .dark * {
+  background: #fffaf1 !important;
+  color: #000 !important;
+}
+#col-container {
+  background: #fffaf1;
+  padding: 20px;
+  border-radius: 16px;
+  box-shadow: 0 4px 12px rgba(0,0,0,0.1);
+  margin: auto;
+  max-width: 780px;
+}
+.gr-button {
+  background-color: #d4a373 !important;
+  color: white !important;
+  border-radius: 8px !important;
+  padding: 10px 24px !important;
+  font-weight: bold;
+  transition: background-color 0.3s;
+}
+.gr-button:hover {
+  background-color: #c48f61 !important;
+}
+.gr-textbox, .gr-slider, .gr-radio, .gr-checkbox, .gr-image {
+  background: #fff;
+  border-radius: 8px;
+}
+.gr-gallery {
+  background: #fffaf1;
+  padding: 10px;
+  border-radius: 12px;
+}
+.gr-gallery .gallery-item Figcaption,
+.gr-gallery .gallery-item figcaption {
+  width:420px !important;
+  word-wrap:break-word !important;
+}
+.gradio-spinner { display: none !important; }
+#custom-loader {
+  align-items: center;
+  justify-content: center;
+  font-weight: bold;
+  margin: 12px 0;
+  position: fixed;
+  z-index: 9999;
+}
+.block.svelte-11xb1hd {
+  background: #efd1bf !important;
+}
+span.svelte-g2oxp3, label.svelte-5ncdh7.svelte-5ncdh7.svelte-5ncdh7 {
+  color: #915325 !important;
+}
+.svelte-zyxd38 g {
+  display: none !important;
+}
+.secondary.svelte-1ixn6qd {
+  background: #dca08a !important;
+  color: #631c00 !important;
+}
+:root {
+  --color-accent: #a57659;
+}
+.max_value.svelte-10lj3xl.svelte-10lj3xl, span.min_value {
+  color: #a54618 !important;
+}
+body.gradio-running #custom-loader { display: flex; }
+#custom-loader, .loading-text {
+width: auto !important;
+height: auto !important;
+}
+@keyframes fadeLetter {
+  0%,100% { opacity: 1; }
+  50%     { opacity: 0.2; }
+}
+#custom-loader .loading-text span {
+  display: inline-block;
+  animation: fadeLetter 1.8s ease-in-out infinite;
+  font-size:3em;
+}
+#custom-loader img {
+  width: 64px;
+  height: 64px;
+  border-radius: 50%;
+  margin-left: 8px;
+  display: inline-block;
+  animation: jump 2s infinite ease-in-out;
+  vertical-align: middle;
+}
+.svelte-zyxd38{
+ width: 100% !important;
+ height: 100% !important;
+}
+    @keyframes jump {
+      0%, 100% { transform: translateY(10px); opacity: 1;}
+      50%      { transform: translateY(-10px); opacity: 1;}
+    }
+.nobackground, .nobackground div, .nobackground.parent.parent.parent {
+  background-color: transparent !important;
+}
+progress::-webkit-progress-value {
+  background-color: #a57659 !important;
+}
+progress::-moz-progress-bar {
+  background-color: #a57659 !important;
+}
+.gradio-progress .progress-bar,
+.gradio-progress-bar {
+  background-color: #a57659 !important;
+}
+
+"""
+
+with gr.Blocks(css=css, theme=gr.themes.Default(font=[gr.themes.GoogleFont("Playpen Sans Hebrew"), "Arial", "sans-serif"])) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.HTML('<section class="nobackground"><h2>SDXL – Re:cocoamixXL3 (coamixXL3) Demo</h2><br>The log is shared with other. (No more than 10 images will be displayed in history.)<br>Please use this model at your own risk. I am not responsible in any way for any problems with the generated images.</section>')
+        gr.HTML('<section class="nobackground"><a href="https://civitai.com/models/1553716?modelVersionId=1855218" target="_blank">Link: Civitai</a></section>')
+
+        with gr.Row():
+            prompt = gr.Textbox(lines=1, placeholder="Prompt…", value="1girl, cocoart, masterpiece, anime, high quality,", label="Prompt")
+            neg    = gr.Textbox(lines=1, placeholder="Negative prompt", value="low quality, worst quality, bad, bad lighting, lowres, error, miss stroke, smoke, ugly, extra digits, creepy, imprecise, blurry,", label="Negative prompt")
+        with gr.Row():
+            seed_sl = gr.Slider(0, MAX_SEED, step=1, value=0, label="Seed")
+            rand    = gr.Checkbox(True, label="Randomize seed")
+        with gr.Row():
+            width  = gr.Slider(256, 512, step=32, value=512, label="Width")
+            height = gr.Slider(256, 768, step=32, value=512, label="Height")
+        with gr.Row():
+            cfg    = gr.Slider(1.0, 30.0, step=0.5, value=6, label="CFG Scale")
+            steps  = gr.Slider(1, 15, step=1, value=12,   label="Steps")
+        with gr.Row():
+            scheduler_type = gr.Radio(choices=["Euler Ancestral", "DPM++ 2M SDE"], value="Euler Ancestral", label="Scheduler")
+            run = gr.Button("Generate")
+
+        # カスタムローダー
+        gr.HTML(
+            """
+<script>
+window.addEventListener('load', () => {
+  const observer = new MutationObserver(() => {
+    const svg = document.querySelector('svg.svelte-zyxd38');
+    if (!svg) return;
+    // 一度挿入したら再挿入しない
+    if (svg.querySelector('foreignObject#custom-loader-fo')) return;
+
+    const SVG_NS = 'http://www.w3.org/2000/svg';
+    // foreignObject を作成
+    const fo = document.createElementNS(SVG_NS, 'foreignObject');
+    fo.setAttribute('id', 'custom-loader-fo');
+    fo.setAttribute('width', '100%');   // SVG 内の表示エリア幅に合わせて調整
+    fo.setAttribute('height', '100%');  // SVG 内の表示エリア高さに合わせて調整
+    fo.setAttribute('x', '-200');
+    fo.setAttribute('y', '0');
+
+    // HTML 部分を innerHTML で一発挿入
+    fo.innerHTML = `
+      <div id="custom-loader" xmlns="http://www.w3.org/1999/xhtml">
+        <div class="loading-text">
+          <span style="animation-delay:0s">i</span>
+          <span style="animation-delay:0.1s">n</span>
+          <span style="animation-delay:0.2s"> </span>
+          <span style="animation-delay:0.3s">p</span>
+          <span style="animation-delay:0.4s">r</span>
+          <span style="animation-delay:0.5s">o</span>
+          <span style="animation-delay:0.6s">g</span>
+          <span style="animation-delay:0.7s">r</span>
+          <span style="animation-delay:0.8s">e</span>
+          <span style="animation-delay:0.9s">s</span>
+          <span style="animation-delay:1.0s">s</span>
+          <img src="https://huggingface.co/spaces/cocoat/Re.cocoamixXL3/resolve/main/icon.png" width="32" height="32" />
+        </div>
+      </div>
+    `;
+
+    svg.appendChild(fo);
+  });
+  observer.observe(document.body, { childList: true, subtree: true });
+});
+</script>
+            """
+        )
+        img_out = gr.Image(
+            interactive=None, 
+            value=create_dummy_image(width=512, height=512, alpha=0),
+            label="生成画像" 
+        )
+        state   = gr.State([])
+        history_gallery = gr.Gallery(
+            label="生成履歴",
+            columns=4,
+            height=280,
+            show_label=False,
+            interactive=None,
+            type="auto",
+            value=[]
+        )
+        # テーブル部分だけを下にまとめて生HTMLレンダー
+        history_tables = gr.HTML(value="")
+
+    run.click(
+        fn=infer,
+        inputs=[prompt, neg, seed_sl, rand, width, height, cfg, steps, scheduler_type],
+        outputs=[img_out, history_gallery, history_tables]
+    )
+    history_gallery.select(
+        fn=update_history_tables_on_select,
+        inputs=None, # select イベントは自動的にイベントデータ (gr.SelectData) を渡す
+        outputs=[history_tables]
+    )
+
+# ページロード時に history から初期表示
+    demo.load( 
+        fn=lambda: ( # history リストの各要素が (Hub上のファイルパス, キャプション, Space内のファイルパス)
+            [ (item[2], item[1].replace("|-|", "\n")) for item in history if item[2] is not None ], 
+            make_html_table(history[0][1]) if history else "" # 最初のアイテムのキャプションを表示 
+        ), 
+        inputs=[], 
+        outputs=[history_gallery, history_tables] 
+    )
+    
+demo.queue()
+demo.launch()