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import gradio as gr | |
from transformers import pipeline | |
import io, base64 | |
from PIL import Image | |
import numpy as np | |
import tensorflow as tf | |
import mediapy | |
import os | |
import sys | |
from huggingface_hub import snapshot_download | |
image_gen = gr.Interface.load("spaces/multimodalart/latentdiffusion") | |
os.system("git clone https://github.com/google-research/frame-interpolation") | |
sys.path.append("frame-interpolation") | |
from eval import interpolator, util | |
ffmpeg_path = util.get_ffmpeg_path() | |
mediapy.set_ffmpeg(ffmpeg_path) | |
model = snapshot_download(repo_id="akhaliq/frame-interpolation-film-style") | |
interpolator = interpolator.Interpolator(model, None) | |
def generate_story(choice, input_text): | |
query = "<BOS> <{0}> {1}".format(choice, input_text) | |
print(query) | |
generated_text = story_gen(query) | |
generated_text = generated_text[0]['generated_text'] | |
generated_text = generated_text.split('> ')[2] | |
return generated_text | |
def generate_images(text): | |
steps=50 | |
width=256 | |
height=256 | |
num_images=4 | |
diversity=4 | |
image_bytes = image_gen(text, steps, width, height, num_images, diversity) | |
# Algo from spaces/Gradio-Blocks/latent_gpt2_story/blob/main/app.py | |
generated_images = [] | |
for image in image_bytes[1]: | |
image_str = image[0] | |
image_str = image_str.replace("data:image/png;base64,","") | |
decoded_bytes = base64.decodebytes(bytes(image_str, "utf-8")) | |
img = Image.open(io.BytesIO(decoded_bytes)) | |
generated_images.append(img) | |
return generated_images | |
def generate_interpolation(text): | |
times_to_interpolate = 4 | |
generated_images = generate_images(text) | |
generated_images[0].save('frame_0.png') | |
generated_images[1].save('frame_1.png') | |
generated_images[2].save('frame_2.png') | |
generated_images[3].save('frame_3.png') | |
input_frames = ["frame_0.png", "frame_1.png", "frame_2.png", "frame_3.png"] | |
frames = list(util.interpolate_recursively_from_files(input_frames, times_to_interpolate, interpolator)) | |
mediapy.write_video("out.mp4", frames, fps=7) | |
return "out.mp4" | |
demo = gr.Blocks() | |
with demo: | |
input_start_text = gr.Textbox(placeholder='A teddy bear outer space', label="Starting Text") | |
button_gen_video = gr.Button("Generate Video") | |
output_interpolation = gr.Video(label="Generated Video") | |
button_gen_video.click(fn=generate_interpolation, inputs=input_start_text, outputs=output_interpolation) | |
demo.launch(debug=True, enable_queue=True) |