Spaces:
Running
Running
File size: 5,523 Bytes
e547b24 95c9961 e547b24 95c9961 e547b24 1b9717a 95c9961 1b9717a 95c9961 ae718ef e547b24 eac94ad 95c9961 eac94ad 95c9961 eac94ad 95c9961 eac94ad b1f33f8 95c9961 eac94ad e547b24 95c9961 1b9717a 95c9961 e547b24 95c9961 e547b24 95c9961 753d150 95c9961 eac94ad 753d150 95c9961 e547b24 95c9961 e547b24 95c9961 e547b24 02f8cfa 4d6cbec eac94ad 9608c70 eac94ad 9608c70 eac94ad 9608c70 eac94ad 9608c70 73f7edc e547b24 9608c70 bde9638 4d6cbec 02f8cfa 753d150 bde9638 eac94ad 753d150 4d6cbec eac94ad bde9638 eac94ad 4fd1b5f eac94ad 95c9961 eac94ad e547b24 eac94ad 4d6cbec 02f8cfa eac94ad 95c9961 eac94ad e547b24 eac94ad 95c9961 eac94ad 753d150 e547b24 eac94ad |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 |
import gradio as gr
import requests
import io
import random
import os
import time
from PIL import Image
from deep_translator import GoogleTranslator
# Project by Nymbo
API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
API_TOKEN = os.getenv("HF_READ_TOKEN")
headers = {"Authorization": f"Bearer {API_TOKEN}"}
timeout = 9000000
def convert_to_png(image):
"""Convert any image format to true PNG format"""
png_buffer = io.BytesIO()
if image.mode == 'RGBA':
# If image has alpha channel, save as PNG with transparency
image.save(png_buffer, format='PNG', optimize=True)
else:
# Convert to RGB first if not in RGB/RGBA mode
if image.mode != 'RGB':
image = image.convert('RGB')
image.save(png_buffer, format='PNG', optimize=True)
png_buffer.seek(0)
return Image.open(png_buffer)
def query(prompt, is_negative=False, steps=20, cfg_scale=7, sampler="DPM++ 2M Karras",
seed=-1, strength=0.7, width=1024, height=1024):
if not prompt:
return None
key = random.randint(0, 999)
API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN")])
headers = {"Authorization": f"Bearer {API_TOKEN}"}
payload = {
"inputs": prompt,
"is_negative": is_negative,
"steps": steps,
"cfg_scale": cfg_scale,
"seed": seed if seed != -1 else random.randint(1, 1000000000),
"strength": strength,
"parameters": {"width": width, "height": height}
}
try:
response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
response.raise_for_status()
# Convert directly to PNG without intermediate format
img = Image.open(io.BytesIO(response.content))
png_img = convert_to_png(img)
print(f'\033[1mGeneration {key} completed as PNG!\033[0m')
return png_img
except requests.exceptions.RequestException as e:
print(f"API Error: {e}")
if hasattr(e, 'response') and e.response:
if e.response.status_code == 503:
raise gr.Error("503: Model is loading, please try again later")
raise gr.Error(f"{e.response.status_code}: {e.response.text}")
raise gr.Error("Network error occurred")
except Exception as e:
print(f"Image processing error: {e}")
raise gr.Error(f"Image processing failed: {str(e)}")
# Light theme CSS
css = """
#app-container {
max-width: 800px;
margin: 0 auto;
padding: 20px;
background: #ffffff;
}
#prompt-text-input, #negative-prompt-text-input {
font-size: 14px;
background: #f9f9f9;
}
#gallery {
min-height: 512px;
background: #ffffff;
border: 1px solid #e0e0e0;
}
#gen-button {
margin: 10px 0;
background: #4CAF50;
color: white;
}
.accordion {
background: #f5f5f5;
border: 1px solid #e0e0e0;
}
h1 {
color: #333333;
}
"""
with gr.Blocks(theme=gr.themes.Default(primary_hue="green"), css=css) as app:
gr.HTML("<center><h1>BSP Dev Work</h1></center>")
with gr.Column(elem_id="app-container"):
with gr.Row():
with gr.Column(elem_id="prompt-container"):
with gr.Row():
text_prompt = gr.Textbox(
label="Prompt",
placeholder="Prompt",
lines=2,
elem_id="prompt-text-input"
)
with gr.Accordion("Advanced Settings", open=False):
negative_prompt = gr.Textbox(
label="Negative Prompt",
value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",
lines=3
)
with gr.Row():
width = gr.Slider(1024, label="Width", minimum=512, maximum=2048, step=64)
height = gr.Slider(1024, label="Height", minimum=512, maximum=2048, step=64)
with gr.Row():
steps = gr.Slider(4, label="Steps", minimum=4, maximum=100, step=1)
cfg = gr.Slider(7.0, label="CFG Scale", minimum=1.0, maximum=20.0, step=0.5)
with gr.Row():
strength = gr.Slider(0.7, label="Strength", minimum=0.1, maximum=1.0, step=0.01)
seed = gr.Number(-1, label="Seed (-1 for random)")
method = gr.Radio(
["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"],
value="DPM++ 2M Karras",
label="Sampling Method"
)
generate_btn = gr.Button("Generate Image", variant="primary")
with gr.Row():
output_image = gr.Image(
type="pil",
label="Generated PNG Image",
format="png", # Explicitly set output format
elem_id="gallery"
)
generate_btn.click(
fn=query,
inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height],
outputs=output_image
)
app.launch(server_name="0.0.0.0", server_port=7860, share=True) |