msVision_3 / app.py
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import gradio as gr
from transformers import pipeline
from gradio_client import Client # ๊ฐ€์ •: gradio_client ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ๊ฐ€ ์‚ฌ์šฉ ๊ฐ€๋Šฅํ•˜๋‹ค.
# ์ด๋ฏธ์ง€ ์ธ์‹ ํŒŒ์ดํ”„๋ผ์ธ ๋กœ๋“œ
image_model = pipeline("image-classification", model="google/vit-base-patch16-224")
def generate_music(prompt):
# ์Œ์•… ์ƒ์„ฑ API ํ˜ธ์ถœ
client = Client("https://haoheliu-audioldm2-text2audio-text2music.hf.space/")
result = client.predict(
prompt,
prompt, # ์Œ์„ฑ ์ƒ์„ฑ์— ์‚ฌ์šฉ๋  ํ”„๋กฌํ”„ํŠธ
5, # ์Œ์•…์˜ ๊ธธ์ด (์ดˆ)
0, # ๊ฐ€์ด๋˜์Šค ์Šค์ผ€์ผ
5, # ์‹œ๋“œ ๊ฐ’
1, # ์ƒ์„ฑํ•  waveform์˜ ์ˆ˜
fn_index=1 # ํ•จ์ˆ˜ ์ธ๋ฑ์Šค
)
# API ํ˜ธ์ถœ ๊ฒฐ๊ณผ ์ฒ˜๋ฆฌ
return result
def generate_voice(prompt):
# Tango API๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์Œ์„ฑ ์ƒ์„ฑ
client = Client("https://declare-lab-tango.hf.space/")
result = client.predict(
prompt, # ์ด๋ฏธ์ง€ ๋ถ„๋ฅ˜ ๊ฒฐ๊ณผ๋ฅผ ํ”„๋กฌํ”„ํŠธ๋กœ ์‚ฌ์šฉ
100, # Steps
1, # Guidance Scale
api_name="/predict" # API ์—”๋“œํฌ์ธํŠธ ๊ฒฝ๋กœ
)
# Tango API ํ˜ธ์ถœ ๊ฒฐ๊ณผ ์ฒ˜๋ฆฌ
# ์˜ˆ: result์—์„œ ์Œ์„ฑ ํŒŒ์ผ URL ๋˜๋Š” ๋ฐ์ดํ„ฐ ์ถ”์ถœ
return result
def classify_and_generate_voice(uploaded_image):
# ์ด๋ฏธ์ง€ ๋ถ„๋ฅ˜
predictions = image_model(uploaded_image)
top_prediction = predictions[0]['label'] # ๊ฐ€์žฅ ํ™•๋ฅ ์ด ๋†’์€ ๋ถ„๋ฅ˜ ๊ฒฐ๊ณผ
# ์Œ์„ฑ ์ƒ์„ฑ
voice_result = generate_voice(top_prediction)
# ์Œ์•… ์ƒ์„ฑ
music_result = generate_music("Generate music for: " + top_prediction)
# ๋ฐ˜ํ™˜๋œ ์Œ์„ฑ ๋ฐ ์Œ์•… ๊ฒฐ๊ณผ๋ฅผ Gradio ์ธํ„ฐํŽ˜์ด์Šค๋กœ ์ „๋‹ฌ
# ์˜ˆ: voice_result['url'] ๋˜๋Š” voice_result['audio_data'] ๋“ฑ
return top_prediction, voice_result, music_result
# Gradio ์ธํ„ฐํŽ˜์ด์Šค ์ƒ์„ฑ
iface = gr.Interface(
fn=classify_and_generate_voice,
inputs=gr.Image(type="pil"),
outputs=[gr.Label(), gr.Audio()],
title="msVision_3",
description="์ด๋ฏธ์ง€๋ฅผ ์—…๋กœ๋“œํ•˜๋ฉด, ์‚ฌ๋ฌผ์„ ์ธ์‹ํ•˜๊ณ  ํ•ด๋‹นํ•˜๋Š” ์Œ์„ฑ์„ ์ƒ์„ฑํ•ฉ๋‹ˆ๋‹ค.(recognizes the object and generate voice)",
examples=["dog.jpg", "cat.png", "cafe.jpg"] # ์ˆ˜์ •๋œ ๋ถ€๋ถ„: ์ฝค๋งˆ ์ถ”๊ฐ€
)
# ์ธํ„ฐํŽ˜์ด์Šค ์‹คํ–‰
iface.launch()