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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 yellow face amazon parrot saddles up his horse and goes for a horseback ride across the Amazon river', 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) | |
| examples=[["Three yellow nape amazon parrots dance and celebrate a birthday."],["Two horses trot together across a sunset landscape green field"]] | |
| demo.launch(debug=True, enable_queue=True) | |
| #Not by William Brooks |