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| import torch | |
| print(f"Torch version: {torch.version.cuda}") | |
| from stable_diffusion_tf.stable_diffusion import StableDiffusion as StableDiffusionPy | |
| import gradio as gr | |
| from tensorflow import keras | |
| from PIL import Image | |
| from spectro import wav_bytes_from_spectrogram_image | |
| keras.mixed_precision.set_global_policy("mixed_float16") #float32 | |
| # load keras model | |
| resolution=512 | |
| sd_dreambooth_model_1=StableDiffusionPy(resolution, resolution, download_weights=False, jit_compile=True) | |
| sd_dreambooth_model_1.load_weights_from_pytorch_ckpt("riffusion-model-v1.ckpt") | |
| sd_dreambooth_model_1.diffusion_model.load_weights("dreambooth_riffusion_model_currulao_v1/") | |
| def generate_images(prompt: str, num_steps: int, unconditional_guidance_scale: int, temperature: int): | |
| img = sd_dreambooth_model_1.generate( | |
| prompt, | |
| num_steps=num_steps, | |
| unconditional_guidance_scale=unconditional_guidance_scale, | |
| temperature=temperature, | |
| batch_size=1, | |
| ) | |
| pil_img = Image.fromarray(img[0]) | |
| pil_img.save("img.png") | |
| wav = wav_bytes_from_spectrogram_image(pil_img) | |
| with open("output.wav", "wb") as f: | |
| f.write(wav[0].getbuffer()) | |
| final_video = gr.make_waveform("output.wav", bg_image="img.png") | |
| return final_video | |
| # pass function, input type for prompt, the output for multiple images | |
| gr.Interface( | |
| title="Keras Dreambooth Riffusion-Currulao", | |
| description="""This SD model has been fine-tuned from Riffusion to generate spectrograms of [Currulao](https://en.wikipedia.org/wiki/Music_of_Colombia#Currulao) music. Currulao is a traditional Afro-Colombian music and dance genre, characterized by its rhythmic beats, call-and-response singing, and lively percussion instruments, that holds significant cultural and social importance in Colombia, particularly in the Pacific coast region, as a celebration of African heritage and community identity. | |
| To generate the concept, use the phrase 'a $currulao song' in your prompt. | |
| """, | |
| fn=generate_images, | |
| inputs=[ | |
| gr.Textbox(label="Prompt", value="a $currulao song, lo-fi"), | |
| gr.Slider(label="Inference steps", value=50), | |
| gr.Slider(label="Guidance scale", value=7.5, maximum=15, minimum=0, step=0.5), | |
| gr.Slider(label='Temperature', value=1, maximum=1.5, minimum=0, step=0.1), | |
| ], | |
| outputs=[ | |
| gr.Video(), | |
| ], | |
| examples=[["a $currulao song", 50, 7.5, 1], | |
| ["a $currulao song, lo-fi, nostalgic", 100, 9.5, 0.7]], | |
| ).queue().launch(debug=True) |