import gradio as gr from diffusers import PNDMPipeline, PNDMScheduler import random scheduler = PNDMScheduler(num_train_timesteps=500,beta_schedule="linear") pipeline = PNDMPipeline.from_pretrained("uripper/GIANNIS", scheduler=scheduler) # num_imgs = len(os.listdir("\stored_images")) # imgs = os.listdir("\stored_images") def generate_img(): random_words = ["blue", "bear", "math", "pi", "apple", "cheese", "monkey", "yellow", "grape", "banana", "orange", "dog", "cat", "fish", "bird", "mouse", "horse", "cow", "sheep", "pig", "chicken", "duck", "frog", "snake", "turtle", "elephant", "lion", "tiger", "giraffe", "zebra", "monkey", "ant", "bee", "butterfly", "camel", "crocodile", "dolphin", "duck", "eagle", "fish", "flamingo", "fox", "frog", "giraffe", "goat", "goldfish", "hamster", "hippopotamus", "horse", "kangaroo", "kitten", "lion", "lobster", "monkey", "octopus", "owl", "panda", "parrot", "penguin", "pig", "puppy", "rabbit", "raccoon", "rhinoceros", "scorpion", "seal", "shark", "snail", "snake", "spider", "squirrel", "swan", "tiger", "whale", "wolf", "zebra"] ran_word_1 = random.choice(random_words) ran_word_2 = random.choice(random_words) ran_word_3 = random.choice(random_words) ran_num = str(random.randint(1, 100)) ran_num2 = str(random.randint(1, 100)) filename = ran_word_1 + "_" + ran_num + "_" + ran_word_2 + "_" + ran_num2 + "_" + ran_word_3 try: pipeline.to("cuda") except: pass images= pipeline().images im = images[0] # im.save(f"GIANNIS\stored_images\{filename}.png") return im # def show_random_image(num_imgs = num_imgs, imgs = imgs): # ran_img = random.randint(1, num_imgs)-1 # display_img = "GIANNIS\\stored_images\\"+imgs[ran_img] # return PIL.Image.open(display_img) # for i in range(100): # generate_img() # When a user clicks button, pipeline will generate an image # iface = gr.Interface(fn=show_random_image, inputs=[], outputs="image") iface = gr.Interface(fn=generate_img, inputs=[], outputs="image") iface.launch()