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| import torch | |
| import os | |
| import random | |
| import gradio as gr | |
| from TTS.api import TTS | |
| from transformers import pipeline | |
| import base64 | |
| from datasets import load_dataset | |
| from diffusers import DiffusionPipeline | |
| from huggingface_hub import login | |
| import numpy as np | |
| import spaces | |
| import time | |
| def guessanImage(model, image): | |
| imgclassifier = pipeline("image-classification", model=model) | |
| if image is not None: | |
| description = imgclassifier(image) | |
| return description | |
| def guessanAge(model, image): | |
| imgclassifier = pipeline("image-classification", model=model) | |
| if image is not None: | |
| description = imgclassifier(image) | |
| return description | |
| def text2speech(text, no, sample): | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| os.environ["COQUI_TOS_AGREED"] = "1" | |
| if sample is None: | |
| sample = "sampleaudio/abraham.wav" | |
| if len(text) > 0: | |
| epoch_time = str(int(time.time())) | |
| tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2") | |
| wav = tts.tts_to_file(text=text, file_path="output-"+epoch_time+".wav", speaker_wav=sample, language="en") | |
| return wav | |
| def ImageGenFromText(text, model): | |
| api_key = os.getenv("fluxauth") | |
| login(token=api_key) | |
| if len(text) > 0: | |
| dtype = torch.bfloat16 | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| MAX_SEED = np.iinfo(np.int32).max | |
| seed = random.randint(0, MAX_SEED) | |
| pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=dtype).to(device) | |
| generator = torch.Generator().manual_seed(seed) | |
| image = pipe( | |
| prompt = text, | |
| width = 512, | |
| height = 512, | |
| num_inference_steps = 4, | |
| generator = generator, | |
| guidance_scale=0.0 | |
| ).images[0] | |
| print(image) | |
| return image | |
| radio1 = gr.Radio(["microsoft/resnet-50", "google/vit-base-patch16-224", "apple/mobilevit-small"], value="microsoft/resnet-50", label="Select a Classifier", info="Image Classifier") | |
| tab1 = gr.Interface( | |
| fn=guessanImage, | |
| inputs=[radio1, gr.Image(type="pil")], | |
| outputs=["text"], | |
| ) | |
| radio2 = gr.Radio(["nateraw/vit-age-classifier"], value="nateraw/vit-age-classifier", label="Select an Age Classifier", info="Age Classifier") | |
| tab2 = gr.Interface( | |
| fn=guessanAge, | |
| inputs=[radio2, gr.Image(type="pil")], | |
| outputs=["text"], | |
| ) | |
| textbox = gr.Textbox(value="good morning pineapple! looking very good very nice!", label="Type text to convert to your voice:") | |
| sampletext = gr.HTML(""" | |
| <h3>If you do not sample your voice my voice will be used as input:<h3> | |
| <audio controls autoplay> | |
| <source src="https://huggingface.co./spaces/Abrahamau/gradiotest/resolve/main/sampleaudio/abraham.wav" type="audio/wav"> | |
| Your browser does not support the audio element. | |
| </audio> | |
| """) | |
| micinput = gr.Audio(sources=['microphone'], type="filepath", format="wav") | |
| outaudio = gr.Audio(show_download_button=True, show_share_button=True) | |
| tab3 = gr.Interface( | |
| fn=text2speech, | |
| inputs=[textbox, sampletext, micinput], | |
| outputs=[outaudio], | |
| ) | |
| radio4 = gr.Radio(["black-forest-labs/FLUX.1-schnell"], value="black-forest-labs/FLUX.1-schnell", label="Select", info="text to image") | |
| tab4 = gr.Interface( | |
| fn=ImageGenFromText, | |
| inputs=["text", radio4], | |
| outputs=["image"], | |
| ) | |
| demo = gr.TabbedInterface([tab1, tab2, tab3, tab4], ["Describe", "Estimage Age", "Speak", "Generate Image"]) | |
| demo.launch() | |