initial commit

app.py

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+from asyncio import constants
+import gradio as gr
+import requests
+import os 
+import re
+import random
+import numpy as np
+from perlin_numpy import generate_fractal_noise_2d
+
+def create_fractal_noise(size,n_octaves, n_layers, seed):
+    """
+    Generate fractal noise using the Perlin noise algorithm.
+    """
+    np.random.seed(0)
+    noise = generate_fractal_noise_2d((256, 256), (8, 8), 5)
+    #reshape
+    n3=np.repeat(n[:,:,np.newaxis],3,axis=2)
+    #change from [-1,1] to [0,255]
+    n3=(n3+1)/2*255
+    return n3
+
+demo = gr.Blocks()
+
+with demo:
+  gr.Markdown("<h1><center>LiteDungeon</center></h1>")
+  gr.Markdown(
+        "<div>Create fractal-like noise (useful for map generation and such)</div>"
+    )
+  
+  with gr.Row():
+    output_story = gr.Textbox(value=default_story,label="story",lines=7)
+
+  with gr.Row():  
+    input_seed = gr.Number(label="seed",value=0)
+    input_size = seed=gr.Number(default=256, label='size')
+    res=gr.Number(default=2, label='res')
+    n_octaves=gr.Number(default=2, label='n-octaves')
+    persistence=gr.Number(default=0.5, label='persistence')
+
+    output_image = gr.outputs.Image(type="filepath", label='Output')
+
+  with gr.Row():
+    b0 = gr.Button("Submit")
+  
+  b0.click(create_fractal_noise,inputs=[input_seed,input_size,res,n_octaves,persistencen],outputs=[output_image])
+  #examples=examples
+
+demo.launch(enable_queue=True, debug=True)

requirements.txt

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+numpy==1.22.3
+git+https://github.com/pvigier/perlin-numpy