Spaces:
Runtime error
Runtime error
Commit
•
76afedf
1
Parent(s):
e9cb859
chore: Update Dockerfile and requirements.txt
Browse filesFormer-commit-id: 0caea23b864f7ac1e3663f3f59551de462daf546
Former-commit-id: 69e7898d5bb389e4e83b2115cd78a7088774cb9c
- Dockerfile +4 -4
- api/requirements.txt +1 -1
- api/routers/sdxl_text_to_image.py +0 -1
- gradio-ui/ui.py +0 -59
- requirements.txt +0 -25
- scripts/inpainting_pipeline.py +0 -1
Dockerfile
CHANGED
@@ -1,14 +1,14 @@
|
|
1 |
# Use the official Python base image
|
2 |
-
FROM python:3.
|
3 |
|
4 |
# Set the initial working directory
|
5 |
-
WORKDIR /
|
6 |
|
7 |
# Copy the requirements.txt file from the api directory
|
8 |
-
COPY api/requirements.txt ./
|
9 |
|
10 |
# Install dependencies specified in requirements.txt
|
11 |
-
RUN pip install
|
12 |
|
13 |
# Create a non-root user and set up the environment
|
14 |
RUN useradd -m -u 1000 user
|
|
|
1 |
# Use the official Python base image
|
2 |
+
FROM python:3.10-slim
|
3 |
|
4 |
# Set the initial working directory
|
5 |
+
WORKDIR /app
|
6 |
|
7 |
# Copy the requirements.txt file from the api directory
|
8 |
+
COPY ../api/requirements.txt ./
|
9 |
|
10 |
# Install dependencies specified in requirements.txt
|
11 |
+
RUN pip install -r requirements.txt
|
12 |
|
13 |
# Create a non-root user and set up the environment
|
14 |
RUN useradd -m -u 1000 user
|
api/requirements.txt
CHANGED
@@ -7,7 +7,7 @@ lightning==2.2.3
|
|
7 |
logfire==0.42.0
|
8 |
Pillow==10.3.0
|
9 |
pydantic==2.7.4
|
10 |
-
torch
|
11 |
utils==1.0.2
|
12 |
uvicorn==0.30.1
|
13 |
boto3
|
|
|
7 |
logfire==0.42.0
|
8 |
Pillow==10.3.0
|
9 |
pydantic==2.7.4
|
10 |
+
torch
|
11 |
utils==1.0.2
|
12 |
uvicorn==0.30.1
|
13 |
boto3
|
api/routers/sdxl_text_to_image.py
CHANGED
@@ -10,7 +10,6 @@ import uuid
|
|
10 |
from diffusers import DiffusionPipeline
|
11 |
import torch
|
12 |
from functools import lru_cache
|
13 |
-
from s3_manager import S3ManagerService
|
14 |
from PIL import Image
|
15 |
import io
|
16 |
from utils import accelerator
|
|
|
10 |
from diffusers import DiffusionPipeline
|
11 |
import torch
|
12 |
from functools import lru_cache
|
|
|
13 |
from PIL import Image
|
14 |
import io
|
15 |
from utils import accelerator
|
gradio-ui/ui.py
DELETED
@@ -1,59 +0,0 @@
|
|
1 |
-
import gradio as gr
|
2 |
-
import requests
|
3 |
-
from pydantic import BaseModel
|
4 |
-
from diffusers.utils import load_image
|
5 |
-
|
6 |
-
|
7 |
-
SDXL_LORA_API_URL = 'http://127.0.0.1:8000/api/v1/product-diffusion/sdxl_v0_lora_inference'
|
8 |
-
|
9 |
-
# Define the InpaintingRequest model
|
10 |
-
class InpaintingRequest(BaseModel):
|
11 |
-
prompt: str
|
12 |
-
num_inference_steps: int
|
13 |
-
guidance_scale: float
|
14 |
-
negative_prompt: str
|
15 |
-
num_images: int
|
16 |
-
mode: str
|
17 |
-
|
18 |
-
def generate_sdxl_lora_image(prompt, negative_prompt, num_inference_steps, guidance_scale, num_images, mode):
|
19 |
-
# Prepare the payload for SDXL LORA API
|
20 |
-
payload = InpaintingRequest(
|
21 |
-
prompt=prompt,
|
22 |
-
negative_prompt=negative_prompt,
|
23 |
-
num_inference_steps=num_inference_steps,
|
24 |
-
guidance_scale=guidance_scale,
|
25 |
-
num_images=num_images,
|
26 |
-
mode=mode
|
27 |
-
).model_dump()
|
28 |
-
|
29 |
-
response = requests.post(SDXL_LORA_API_URL, json=payload)
|
30 |
-
response_json = response.json()
|
31 |
-
url = response_json['url']
|
32 |
-
|
33 |
-
image = load_image(url)
|
34 |
-
return image
|
35 |
-
|
36 |
-
with gr.Blocks(theme='gradio/soft') as demo:
|
37 |
-
with gr.Tab("SDXL LORA TEXT-TO-IMAGE"):
|
38 |
-
with gr.Row():
|
39 |
-
with gr.Column(scale=1):
|
40 |
-
|
41 |
-
prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here")
|
42 |
-
negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Enter negative prompt here")
|
43 |
-
|
44 |
-
|
45 |
-
|
46 |
-
with gr.Column(scale=1):
|
47 |
-
num_inference_steps = gr.Slider(minimum=1, maximum=1000, step=1, value=20, label="Inference Steps")
|
48 |
-
guidance_scale = gr.Slider(minimum=1.0, maximum=10.0, step=0.1, value=7.5, label="Guidance Scale")
|
49 |
-
num_images = gr.Slider(minimum=1, maximum=10, step=1, value=1, label="Number of Images")
|
50 |
-
mode = gr.Dropdown(choices=["s3_json", "b64_json"], value="s3_json", label="Mode")
|
51 |
-
generate_button = gr.Button("Generate Image")
|
52 |
-
|
53 |
-
|
54 |
-
image_preview = gr.Image(label="Generated Image", height=512, width=512,scale=1,show_download_button=True,show_share_button=True,container=True)
|
55 |
-
|
56 |
-
generate_button.click(generate_sdxl_lora_image, inputs=[prompt, negative_prompt, num_inference_steps, guidance_scale, num_images, mode], outputs=[image_preview])
|
57 |
-
|
58 |
-
|
59 |
-
demo.launch()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
requirements.txt
CHANGED
@@ -1,25 +0,0 @@
|
|
1 |
-
diffusers
|
2 |
-
datasets
|
3 |
-
fastapi
|
4 |
-
wandb
|
5 |
-
lightning
|
6 |
-
torchvision
|
7 |
-
pandas
|
8 |
-
numpy
|
9 |
-
rich
|
10 |
-
tqdm
|
11 |
-
transformers
|
12 |
-
fastapi
|
13 |
-
uvicorn
|
14 |
-
matplotlib
|
15 |
-
accelerate
|
16 |
-
torchvision
|
17 |
-
ftfy
|
18 |
-
tensorboard
|
19 |
-
Jinja2
|
20 |
-
datasets
|
21 |
-
peft
|
22 |
-
async-batcher
|
23 |
-
ultralytics
|
24 |
-
opencv-python-headless
|
25 |
-
boto3
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
scripts/inpainting_pipeline.py
CHANGED
@@ -5,7 +5,6 @@ from utils import accelerator, ImageAugmentation
|
|
5 |
import hydra
|
6 |
from omegaconf import DictConfig
|
7 |
from PIL import Image
|
8 |
-
from functools import lru_cache
|
9 |
|
10 |
|
11 |
def load_pipeline(model_name: str, device, enable_compile: bool = True):
|
|
|
5 |
import hydra
|
6 |
from omegaconf import DictConfig
|
7 |
from PIL import Image
|
|
|
8 |
|
9 |
|
10 |
def load_pipeline(model_name: str, device, enable_compile: bool = True):
|