uripper
commited on
Commit
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e521b52
1
Parent(s):
08aced1
trimmed broken code
Browse files
app.py
CHANGED
@@ -1,45 +1,20 @@
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import gradio as gr
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from diffusers import PNDMPipeline, PNDMScheduler
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import random
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scheduler = PNDMScheduler(num_train_timesteps=1100)
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pipeline = PNDMPipeline.from_pretrained("uripper/GIANNIS", scheduler=scheduler)
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# num_imgs = len(os.listdir("\stored_images"))
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# imgs = os.listdir("\stored_images")
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def generate_img():
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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"]
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ran_word_1 = random.choice(random_words)
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ran_word_2 = random.choice(random_words)
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ran_word_3 = random.choice(random_words)
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ran_num = str(random.randint(1, 100))
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ran_num2 = str(random.randint(1, 100))
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filename = ran_word_1 + "_" + ran_num + "_" + ran_word_2 + "_" + ran_num2 + "_" + ran_word_3
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try:
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pipeline.to("cuda")
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except:
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pass
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images= pipeline().images
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im = images[0]
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# im.save(f"GIANNIS\stored_images\{filename}.png")
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return im
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# def show_random_image(num_imgs = num_imgs, imgs = imgs):
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# ran_img = random.randint(1, num_imgs)-1
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# display_img = "GIANNIS\\stored_images\\"+imgs[ran_img]
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# return PIL.Image.open(display_img)
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# for i in range(100):
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# generate_img()
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# When a user clicks button, pipeline will generate an image
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# iface = gr.Interface(fn=show_random_image, inputs=[], outputs="image")
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iface = gr.Interface(fn=generate_img, inputs=[], outputs="image")
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iface.launch()
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import gradio as gr
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from diffusers import PNDMPipeline, PNDMScheduler
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scheduler = PNDMScheduler(num_train_timesteps=1100)
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pipeline = PNDMPipeline.from_pretrained("uripper/GIANNIS", scheduler=scheduler)
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def generate_img():
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try:
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pipeline.to("cuda")
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except:
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pass
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images= pipeline().images
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im = images[0]
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return im
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iface = gr.Interface(fn=generate_img, inputs=[], outputs="image")
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iface.launch()
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