𝐁𝐋𝐀𝐂𝐊 𝐂𝐘𝐁𝐄𝐑 𝐅𝐎𝐑𝐂𝐄
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❤️ AUTO REACTION (FOR CHANNEL).👀 Command:
*
var request2 =JSON.parse(request)
if(request2.channel_post){
var msgid = request2.channel_post.message_id
var ch = request2.channel_post.sender_chat.id
var myEmoji = ["👍", "👎", "❤", "🔥", "🥰", "👏", "😁", "🤔", "🤯", "😱", "🤬", "😢", "🎉", "🤩", "🤮", "💩", "🙏", "👌", "🕊", "🤡", "🥱", "🥴", "😍", "🐳", "❤🔥", "🌚", "🌭", "💯", "🤣", "⚡", "🍌", "🏆", "💔", "🤨", "😐", "🍓", "🍾", "💋", "🖕", "😈", "😴", "😭", "🤓", "👻", "👨💻", "👀", "🎃", "🙈", "😇", "😨", "🤝", "✍", "🤗", "🫡", "🎅", "🎄", "☃", "💅", "🤪", "🗿", "🆒", "💘", "🙉", "🦄", "😘", "💊", "🙊", "😎", "👾", "🤷♂", "🤷", "🤷♀", "😡"]
var doEmoji = myEmoji[Math.floor(Math.random() * myEmoji.length)];
HTTP.post({
url: "https://api.telegram.org/bot" + bot.token + "/setMessageReaction",
body: {
chat_id: ch,
message_id: msgid,
reaction: JSON.stringify([
{
type: "emoji",
emoji: doEmoji,
is_big: true
}
])
}
});
}🚀 How to Generate Ghibli Images Using your Python Code?
from diffusers import StableDiffusionImg2ImgPipeline
import torch
from PIL import Image
import io
from google.colab import files
import matplotlib.pyplot as plt
import time
# Load model function
def load_model():
model_id = "nitrosocke/Ghibli-Diffusion" # Correct model ID
dtype = torch.float16 if torch.cuda.is_available() else torch.float32
print("Loading model...")
pipe = StableDiffusionImg2ImgPipeline.from_pretrained(model_id, torch_dtype=dtype)
pipe.to("cuda" if torch.cuda.is_available() else "cpu")
pipe.enable_attention_slicing() # Optimize memory usage
print("Model loaded!")
return pipe
# Function to generate Ghibli-style image
def generate_ghibli_image(image, pipe, strength):
image = image.convert("RGB")
image = image.resize((512, 512)) # Ensure proper size
prompt = "Ghibli-style anime painting, soft pastel colors, highly detailed, masterpiece"
print("Generating image...")
start_time = time.time()
result = pipe(prompt=prompt, image=image, strength=strength).images[0]
print(f"Image generated in {time.time() - start_time:.2f} seconds!")
return result
# Check for GPU
gpu_info = "GPU is available!" if torch.cuda.is_available() else "Warning: GPU not available. Processing will be slow."
print(gpu_info)
# Load the model
pipe = load_model()
# Upload image section
print("Please upload your image file:")
uploaded = files.upload()
if uploaded:
file_name = list(uploaded.keys())[0]
image = Image.open(io.BytesIO(uploaded[file_name]))
# Display original image
plt.figure(figsize=(5, 5))
plt.imshow(image)
plt.title("Original Image")
plt.axis('off')
plt.show()
# Ask for strength input with error handling
while True:
try:
strength = float(input("Enter stylization strength (0.3-0.8, recommended 0.6): "))
strength = max(0.3, min(0.8, strength)) # Clamp between 0.3 and 0.8
break
except ValueError:
print("Invalid input. Please enter a number between 0.3 and 0.8.")
# Generate and display the result
result_img = generate_ghibli_image(image, pipe, strength)
plt.figure(figsize=(5, 5))
plt.imshow(result_img)
plt.title("Ghibli Portrait")
plt.axis('off')
plt.show()
# Save the output image and offer download
output_filename = f"ghibli_portrait_{file_name}"
result_img.save(output_filename)
files.download(output_filename)
print(f"Image saved as {output_filename} and download initiated!")
else:
print("No file was uploaded. Please run the cell again and upload an image.")
Argentina loses today's match, our Raiful Bro will reveal his girlfriend's picture.
