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Image2Body_gradio

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yeq6x commited on Jul 6

Commit

721391f

•

1 Parent(s): dd5dfc8

prepare spaces

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Files changed (13) hide show

.dockerignore +7 -0
Dockerfile.backend +3 -1
README.md +0 -0
app.py +2 -2
docker-compose.yml +3 -3
anime.py → scripts/anime.py +3 -4
data.py → scripts/data.py +0 -0
generate_prompt.py → scripts/generate_prompt.py +0 -0
hf_utils.py → scripts/hf_utils.py +0 -0
lineart_util.py → scripts/lineart_util.py +1 -1
model.py → scripts/model.py +1 -1
process_utils.py → scripts/process_utils.py +3 -3
templates/index.html +0 -60

.dockerignore ADDED Viewed

	@@ -0,0 +1,7 @@

+models/
+__pycache__/
+venv/
+output/
+hf_gradio/
+hf_cache/
+wd14_tagger_model/

Dockerfile.backend CHANGED Viewed

@@ -30,6 +30,8 @@ RUN apt -y install libopencv-dev
 RUN pip install --no-cache-dir -r requirements.txt
 RUN pip install --no-dependencies transformers
-EXPOSE 5000
 CMD ["python", "app.py", "--use_gpu"]

 RUN pip install --no-cache-dir -r requirements.txt
 RUN pip install --no-dependencies transformers
+COPY . /app
+EXPOSE 80
 CMD ["python", "app.py", "--use_gpu"]

README.md ADDED Viewed

File without changes

app.py CHANGED Viewed

@@ -13,7 +13,7 @@ import queue
 import threading
 import uuid
 import concurrent.futures
-from process_utils import *
 app = Flask(__name__)
 # app.secret_key = 'super_secret_key'
@@ -190,4 +190,4 @@ if __name__ == '__main__':
     args = parser.parse_args()
     initialize(args.use_local, args.use_gpu)
-    socketio.run(app, debug=True, host='0.0.0.0', port=5000)

 import threading
 import uuid
 import concurrent.futures
+from scripts.process_utils import *
 app = Flask(__name__)
 # app.secret_key = 'super_secret_key'
     args = parser.parse_args()
     initialize(args.use_local, args.use_gpu)
+    socketio.run(app, debug=True, host='0.0.0.0', port=80)

docker-compose.yml CHANGED Viewed

@@ -4,9 +4,9 @@ services:
       context: .
       dockerfile: Dockerfile.backend
     ports:
-      - "5000:5000"
-    volumes:
-      - .:/app
     env_file:
       - .env
     deploy:

       context: .
       dockerfile: Dockerfile.backend
     ports:
+      - "80:5000"
+    # volumes:
+    #   - .:/app
     env_file:
       - .env
     deploy:

anime.py → scripts/anime.py RENAMED Viewed

@@ -6,10 +6,9 @@ Example:
 import os
 import torch
-from torchvision import transforms
-from data import get_image_list, get_transform
-from model import create_model
-from data import read_img_path, tensor_to_img, save_image
 import argparse
 from tqdm.auto import tqdm
 from kornia.enhance import equalize_clahe

 import os
 import torch
+from scripts.data import get_image_list, get_transform
+from scripts.model import create_model
+from scripts.data import tensor_to_img, save_image
 import argparse
 from tqdm.auto import tqdm
 from kornia.enhance import equalize_clahe

data.py → scripts/data.py RENAMED Viewed

File without changes

generate_prompt.py → scripts/generate_prompt.py RENAMED Viewed

File without changes

hf_utils.py → scripts/hf_utils.py RENAMED Viewed

File without changes

lineart_util.py → scripts/lineart_util.py RENAMED Viewed

@@ -1,7 +1,7 @@
 import cv2
 import numpy as np
 from PIL import Image
-from anime import generate_sketch
 def pad64(x):
     return int(np.ceil(float(x) / 64.0) * 64 - x)

 import cv2
 import numpy as np
 from PIL import Image
+from scripts.anime import generate_sketch
 def pad64(x):
     return int(np.ceil(float(x) / 64.0) * 64 - x)

model.py → scripts/model.py RENAMED Viewed

@@ -2,7 +2,7 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 import functools
-from hf_utils import download_file
 class UnetGenerator(nn.Module):
     """Create a Unet-based generator"""

 import torch.nn as nn
 import torch.nn.functional as F
 import functools
+from scripts.hf_utils import download_file
 class UnetGenerator(nn.Module):
     """Create a Unet-based generator"""

process_utils.py → scripts/process_utils.py RENAMED Viewed

@@ -4,14 +4,14 @@ import base64
 from PIL import Image
 import cv2
 import numpy as np
-from generate_prompt import load_wd14_tagger_model, generate_tags, preprocess_image as wd14_preprocess_image
-from lineart_util import scribble_xdog, get_sketch, canny
 import torch
 from diffusers import StableDiffusionPipeline, StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler, AutoencoderKL
 import gc
 from peft import PeftModel
 from dotenv import load_dotenv
-from hf_utils import download_file
 # グローバル変数
 use_local = False

 from PIL import Image
 import cv2
 import numpy as np
+from scripts.generate_prompt import load_wd14_tagger_model, generate_tags, preprocess_image as wd14_preprocess_image
+from scripts.lineart_util import scribble_xdog, get_sketch, canny
 import torch
 from diffusers import StableDiffusionPipeline, StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler, AutoencoderKL
 import gc
 from peft import PeftModel
 from dotenv import load_dotenv
+from scripts.hf_utils import download_file
 # グローバル変数
 use_local = False

templates/index.html DELETED Viewed

@@ -1,60 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>Scribble Image Generator</title>
-    <style>
-        body { font-family: Arial, sans-serif; max-width: 800px; margin: 0 auto; padding: 20px; }
-        .image-container { display: flex; justify-content: space-between; margin-top: 20px; }
-        .image-container img { max-width: 48%; height: auto; }
-        #loading { display: none; }
-    </style>
-</head>
-<body>
-    <h1>Scribble Image Generator</h1>
-    <form id="upload-form">
-        <input type="file" id="file-input" accept="image/*" required>
-        <br><br>
-        <label for="threshold">Threshold:</label>
-        <input type="number" id="threshold" name="threshold" value="20" min="1" max="64">
-        <br><br>
-        <label for="processor_res">Processor Resolution:</label>
-        <input type="number" id="processor_res" name="processor_res" value="2048" min="64" max="2048">
-        <br><br>
-        <button type="submit">Generate Scribble</button>
-    </form>
-    <div id="loading">Processing...</div>
-    <div class="image-container">
-        <img id="original-image" alt="Original Image">
-        <img id="scribble-image" alt="Scribble Image">
-    </div>
-    <script>
-        document.getElementById('upload-form').addEventListener('submit', function(e) {
-            e.preventDefault();
-            var formData = new FormData();
-            formData.append('file', document.getElementById('file-input').files[0]);
-            formData.append('threshold', document.getElementById('threshold').value);
-            formData.append('processor_res', document.getElementById('processor_res').value);
-            document.getElementById('loading').style.display = 'block';
-            fetch('/process', {
-                method: 'POST',
-                body: formData
-            })
-            .then(response => response.json())
-            .then(data => {
-                document.getElementById('original-image').src = 'data:image/png;base64,' + data.original_image;
-                document.getElementById('scribble-image').src = 'data:image/png;base64,' + data.scribble_image;
-                document.getElementById('loading').style.display = 'none';
-            })
-            .catch(error => {
-                console.error('Error:', error);
-                document.getElementById('loading').style.display = 'none';
-            });
-        });
-    </script>
-</body>
-</html>