Duplicate from phenomenon1981/DreamlikeArt-Diffusion-1.0

.gitattributes

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README.md

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+---
+title: DreamlikeArt-Diffusion 1.0
+emoji: 📈
+colorFrom: blue
+colorTo: yellow
+sdk: gradio
+sdk_version: 3.16.1
+app_file: app.py
+pinned: false
+duplicated_from: phenomenon1981/DreamlikeArt-Diffusion-1.0
+---
+---
+title: DreamlikeArt-Diffusion .0
+emoji: 📈
+colorFrom: blue
+colorTo: yellow
+sdk: gradio
+sdk_version: 3.16.1
+app_file: app.py

app.py

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+import gradio as gr
+import os 
+import sys
+from pathlib import Path
+import random
+import string
+import time
+from queue import Queue
+queue = Queue()
+
+text_gen=gr.Interface.load("spaces/Omnibus/MagicPrompt-Stable-Diffusion")
+proc1=gr.Interface.load("models/dreamlike-art/dreamlike-photoreal-2.0")
+proc5=gr.Interface.load("models/dreamlike-art/dreamlike-diffusion-1.0")
+
+def reset_queue_periodically():
+    start_time = time.time()
+    while True:
+        if time.time() - start_time > 300: # 300 seconds = 5 minutes
+            queue.queue.clear()
+            start_time = time.time()
+        time.sleep(1)
+
+def add_random_noise(prompt, noise_level=0.07):
+    # Get the percentage of characters to add as noise
+    percentage_noise = noise_level * 5
+    # Get the number of characters to add as noise
+    num_noise_chars = int(len(prompt) * (percentage_noise/100))
+    # Get the indices of the characters to add noise to
+    noise_indices = random.sample(range(len(prompt)), num_noise_chars)
+    # Add noise to the selected characters
+    prompt_list = list(prompt)
+    for index in noise_indices:
+        prompt_list[index] = random.choice(string.ascii_letters + string.punctuation)
+    return "".join(prompt_list)
+
+queue_length_counter = 0
+
+def send_it1(inputs, noise_level, proc1=proc1):
+    global queue_length_counter
+    prompt_with_noise = add_random_noise(inputs, noise_level)
+    if queue_length_counter >= 15:
+        if not queue.empty():
+            queue.queue.clear()
+        queue_length_counter = 0
+    output1 = proc1(prompt_with_noise)
+    queue_length_counter += 1
+    return output1
+    time.sleep(1)
+
+def send_it2(inputs, noise_level, proc1=proc1):
+    global queue_length_counter
+    prompt_with_noise = add_random_noise(inputs, noise_level)
+    if queue_length_counter >= 15:
+        if not queue.empty():
+            queue.queue.clear()
+        queue_length_counter = 0
+    output2 = proc1(prompt_with_noise)
+    queue_length_counter += 1
+    return output2
+    time.sleep(1)
+
+def send_it3(inputs, noise_level, proc1=proc1):
+    global queue_length_counter
+    prompt_with_noise = add_random_noise(inputs, noise_level)
+    if queue_length_counter >= 15:
+        if not queue.empty():
+            queue.queue.clear()
+        queue_length_counter = 0
+    output3 = proc1(prompt_with_noise)
+    queue_length_counter += 1
+    return output3
+    time.sleep(1)
+
+def send_it4(inputs, noise_level, proc1=proc1):
+    global queue_length_counter
+    prompt_with_noise = add_random_noise(inputs, noise_level)
+    if queue_length_counter >= 15:
+        if not queue.empty():
+            queue.queue.clear()
+        queue_length_counter = 0
+    output4 = proc1(prompt_with_noise)
+    queue_length_counter += 1
+    return output4
+    time.sleep(1)
+
+def send_it5(inputs, noise_level, proc5=proc5):
+    global queue_length_counter
+    prompt_with_noise = add_random_noise(inputs, noise_level)
+    if queue_length_counter >= 15:
+        if not queue.empty():
+            queue.queue.clear()
+        queue_length_counter = 0
+    output5 = proc5(prompt_with_noise)
+    queue_length_counter += 1
+    return output5
+    time.sleep(1)
+
+def send_it6(inputs, noise_level, proc5=proc5):
+    global queue_length_counter
+    prompt_with_noise = add_random_noise(inputs, noise_level)
+    if queue_length_counter >= 15:
+        if not queue.empty():
+            queue.queue.clear()
+        queue_length_counter = 0
+    output6 = proc5(prompt_with_noise)
+    queue_length_counter += 1
+    return output6
+    time.sleep(1)
+
+def send_it7(inputs, noise_level, proc5=proc5):
+    global queue_length_counter
+    prompt_with_noise = add_random_noise(inputs, noise_level)
+    if queue_length_counter >= 15:
+        if not queue.empty():
+            queue.queue.clear()
+        queue_length_counter = 0
+    output7 = proc5(prompt_with_noise)
+    queue_length_counter += 1
+    return output7
+    time.sleep(1)
+
+def send_it8(inputs, noise_level, proc5=proc5):
+    global queue_length_counter
+    prompt_with_noise = add_random_noise(inputs, noise_level)
+    if queue_length_counter >= 15:
+        if not queue.empty():
+            queue.queue.clear()
+        queue_length_counter = 0
+    output8 = proc5(prompt_with_noise)
+    queue_length_counter += 1
+    return output8
+    time.sleep(1)
+
+
+
+def get_prompts(prompt_text):
+    global queue_length_counter
+    if queue_length_counter >= 15:
+        if not queue.empty():
+            queue.queue.clear()
+        queue_length_counter = 0
+    output = text_gen(prompt_text)
+    queue_length_counter += 1
+    return output
+    time.sleep(1)
+
+
+with gr.Blocks() as myface:
+    with gr.Row():
+
+        input_text=gr.Textbox(label="Short Prompt")
+        see_prompts=gr.Button("Magic Prompt")
+    with gr.Row():
+
+        prompt=gr.Textbox(label="Enter Prompt")
+        noise_level=gr.Slider(minimum=0.1, maximum=3, step=0.1, label="Noise Level: Controls how much randomness is added to the input before it is sent to the model. Higher noise level produces more diverse outputs, while lower noise level produces similar outputs.")
+        run=gr.Button("Generate")
+
+    with gr.Row():
+        like_message = gr.Button("❤️ Press the Like Button if you enjoy my space! ❤️")
+    with gr.Row():
+        output1=gr.Image(label="Dreamlike Photoreal 2.0")
+        output2=gr.Image(label="Dreamlike Photoreal 2.0")
+    with gr.Row():
+        output3=gr.Image(label="Dreamlike Photoreal 2.0")
+        output4=gr.Image(label="Dreamlike Photoreal 2.0")
+    with gr.Row():
+        output5=gr.Image(label="Dreamlike Diffusion 1.0")
+        output6=gr.Image(label="Dreamlike Diffusion 1.0")
+    with gr.Row():
+        output7=gr.Image(label="Dreamlike Diffusion 1.0")
+        output8=gr.Image(label="Dreamlike Diffusion 1.0")
+
+    
+    run.click(send_it1, inputs=[prompt, noise_level], outputs=[output1])
+    run.click(send_it2, inputs=[prompt, noise_level], outputs=[output2])
+    run.click(send_it3, inputs=[prompt, noise_level], outputs=[output3])
+    run.click(send_it4, inputs=[prompt, noise_level], outputs=[output4])
+    run.click(send_it5, inputs=[prompt, noise_level], outputs=[output5])
+    run.click(send_it6, inputs=[prompt, noise_level], outputs=[output6])
+    run.click(send_it7, inputs=[prompt, noise_level], outputs=[output7])
+    run.click(send_it8, inputs=[prompt, noise_level], outputs=[output8])
+    see_prompts.click(get_prompts, inputs=[input_text], outputs=[prompt])
+
+
+
+myface.queue(concurrency_count=8)
+myface.launch(enable_queue=True, inline=True)
+while True:
+    if queue.qsize() >= 20:
+        queue.queue.clear()
+    time.sleep(30)

requirements.txt

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+accelerate==0.12.0
+gradio