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import gradio as gr
import requests
import os
from PIL import Image
from io import BytesIO
from tqdm import tqdm
import time
# Defining the repository information and the trigger word
repo = "artificialguybr/TshirtDesignRedmond-V2"
trigger_word = "T shirt design, TshirtDesignAF, "
def generate_image(prompt):
print("Generating image with prompt:", prompt)
api_url = f"https://api-inference.huggingface.co/models/{repo}"
#token = os.getenv("API_TOKEN") # Uncomment and use your Hugging Face API token
headers = {
#"Authorization": f"Bearer {token}"
}
full_prompt = f"{prompt} {trigger_word}"
payload = {
"inputs": full_prompt,
"parameters": {
"negative_prompt": "(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art:1.4), (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name:1.2), (blur, blurry, grainy), morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur:1.3), (3D ,3D Game, 3D Game Scene, 3D Character:1.1), (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities:1.3)",
"num_inference_steps": 30,
"scheduler": "DPMSolverMultistepScheduler"
},
}
error_count = 0
pbar = tqdm(total=None, desc="Loading model")
while True:
print("Sending request to API...")
response = requests.post(api_url, headers=headers, json=payload)
print("API response status code:", response.status_code)
if response.status_code == 200:
print("Image generation successful!")
return Image.open(BytesIO(response.content)) # Changed to match the first code
elif response.status_code == 503:
time.sleep(1)
pbar.update(1)
elif response.status_code == 500 and error_count < 5:
time.sleep(1)
error_count += 1
else:
print("API Error:", response.status_code)
raise Exception(f"API Error: {response.status_code}")
iface = gr.Interface(
fn=generate_image,
inputs=gr.Textbox(lines=2, placeholder="Type your prompt here..."),
outputs="image",
title="Clothe Designs to use in our img2img model",
description="Make designs for your clothes",
examples=[["Cute Panda"], ["Skull"]]
)
print("Launching Gradio interface...")
iface.launch() |