removing lab1

lab1.py

@@ -1,93 +0,0 @@
-'''
-1. Accept image via Gradio 
-    * image will come out an a numpy array
-    Done!
-2. resize image 
-    * Solved with PIL 
-3. split image into blocks 
-    * Solved with PIL
-4. find color of the square 
-    * potentially solved with PIL 
-6. Find image with similar color profile
-    *need database 
-7. Place image in the new output image
-    * can be done with PIL
-'''
-
-import gradio as gr
-import numpy as np
-from PIL import Image
-from SSIM_PIL import compare_ssim
-
-# Define a function that applies a sepia filter to an image.
-def mosiac(input_img):
-    pil_img = Image.fromarray(input_img)
-
-    width, height = pil_img.size
-
-    #resizing the image
-    if width != height: 
-        if width < height:
-            #make height the same as width
-            box = (0, 0, width, width)
-        elif height < width: 
-            #make width the same as height
-            box = (0, 0, height, height)
-        pil_img = pil_img.crop(box)
-
-    width, height = pil_img.size
-    dims = np.pow(np.floor(np.sqrt(np.sqrt(width))), 4)
-    box = (0, 0, dims, dims)
-    cropped_original = pil_img.crop(box)
-    pil_img = cropped_original.copy()
-
-    quant_img = pil_img.quantize(colors = 100)
-    
-    #putting a grid on the image
-
-    #gridsize
-    grid_size = 16
-
-    #size of each image
-    img_size = int(width/grid_size)
-    
-    for column in range(0, grid_size):
-        for row in range(0, grid_size):
-            box = (int((row - 1) * img_size), int((column - 1) * img_size), int(row * img_size), int(column * img_size))
-            tile = quant_img.crop(box)
-            tile = tile.quantize(colors=3, method=2)
-            tile_rgb = tile.getpalette()[:9]
-            first_flag = True
-            with open("imageRGBs.txt", "r") as database:
-                for line in database: 
-                    rgb, img_num = line.split(';')
-                    rgb = rgb.split(' ')
-                    rgb = list(map(int, rgb))
-                    
-                    difference = np.abs((tile_rgb[0] - rgb[0]) + (tile_rgb[1] - rgb[1]) + (tile_rgb[2] - rgb[2]))
-                    difference = difference + np.abs((tile_rgb[3] - rgb[3]) + (tile_rgb[4] - rgb[4]) + (tile_rgb[5] - rgb[5])) * .5
-                    difference = difference + np.abs((tile_rgb[6] - rgb[6]) + (tile_rgb[7] - rgb[7]) + (tile_rgb[8] - rgb[8])) * .333
-                    
-                    if first_flag:
-                        min_diff = difference
-                        min_img_num = img_num.replace("\n", "")
-                        first_flag = False
-                    else: 
-                        if (min_diff > difference): 
-                            min_diff = difference 
-                            min_img_num = img_num.replace("\n", "")
-            replace_image = Image.open("images\\" + min_img_num)
-            replace_image = replace_image.resize((img_size, img_size))
-            pil_img.paste(replace_image, box)
-    
-    ssim_score = compare_ssim(pil_img, cropped_original)
-    print(ssim_score)
-
-    return pil_img
-
-# Create a Gradio interface that takes an image input, runs it through the sepia function, and returns the filtered image.
-demo = gr.Interface(mosiac, gr.Image(), "image")
-
-# Launch the interface.
-if __name__ == "__main__":
-    demo.launch(show_error=True)