Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
@@ -1,64 +1,87 @@
|
|
1 |
-
# import part
|
2 |
import streamlit as st
|
3 |
from transformers import pipeline
|
4 |
-
import
|
|
|
|
|
|
|
5 |
|
6 |
-
#
|
7 |
-
|
8 |
-
def img2text(url):
|
9 |
-
image_to_text_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
|
10 |
-
text = image_to_text_model(url)[0]["generated_text"]
|
11 |
-
return text
|
12 |
|
13 |
-
#
|
14 |
-
|
15 |
-
|
16 |
-
|
17 |
-
|
|
|
|
|
18 |
|
19 |
-
|
20 |
-
def
|
21 |
-
|
22 |
-
audio_data = pipe(story_text)
|
23 |
-
return audio_data
|
24 |
|
|
|
|
|
|
|
|
|
|
|
|
|
25 |
|
26 |
-
#
|
|
|
27 |
|
28 |
-
|
29 |
-
|
30 |
-
st.header("
|
31 |
-
|
32 |
-
|
33 |
-
|
34 |
-
|
35 |
-
|
36 |
-
|
37 |
-
with open(uploaded_file.name, "wb") as file:
|
38 |
-
file.write(bytes_data)
|
39 |
-
st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
|
40 |
|
|
|
|
|
|
|
|
|
41 |
|
42 |
-
|
43 |
-
|
44 |
-
|
45 |
-
|
46 |
-
|
47 |
-
|
48 |
-
|
49 |
-
|
50 |
-
|
51 |
-
|
52 |
-
|
53 |
-
|
54 |
-
|
55 |
-
|
56 |
-
|
57 |
-
|
58 |
-
|
59 |
-
|
60 |
-
|
61 |
-
|
62 |
-
|
63 |
-
|
64 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
import streamlit as st
|
2 |
from transformers import pipeline
|
3 |
+
from datasets import load_dataset
|
4 |
+
from PIL import Image
|
5 |
+
import numpy as np
|
6 |
+
from collections import Counter
|
7 |
|
8 |
+
# 设置页面标题
|
9 |
+
st.set_page_config(page_title="🏠 Airbnb Design Advisor", layout="wide")
|
|
|
|
|
|
|
|
|
10 |
|
11 |
+
# 缓存模型和数据集
|
12 |
+
@st.cache_resource
|
13 |
+
def load_models():
|
14 |
+
return {
|
15 |
+
"detector": pipeline("object-detection", model="facebook/detr-resnet-50"),
|
16 |
+
"generator": pipeline("text2text-generation", model="google/flan-t5-base")
|
17 |
+
}
|
18 |
|
19 |
+
@st.cache_data
|
20 |
+
def load_data():
|
21 |
+
return load_dataset("AntZet/home_decoration_objects_images")['train'].to_pandas()
|
|
|
|
|
22 |
|
23 |
+
# 颜色提取函数
|
24 |
+
def get_colors(img, n=3):
|
25 |
+
arr = np.array(img.resize((50,50)))
|
26 |
+
from sklearn.cluster import KMeans
|
27 |
+
return [f"#{int(c[0]):02x}{int(c[1]):02x}{int(c[2]):02x}"
|
28 |
+
for c in KMeans(n_clusters=n).fit(arr.reshape(-1,3)).cluster_centers_]
|
29 |
|
30 |
+
# 主界面
|
31 |
+
st.title("AI-Powered Airbnb Design Advisor")
|
32 |
|
33 |
+
# 侧边栏控制
|
34 |
+
with st.sidebar:
|
35 |
+
st.header("Settings")
|
36 |
+
style = st.selectbox(
|
37 |
+
"Select Style",
|
38 |
+
["industrial", "scandinavian", "bohemian", "modern"],
|
39 |
+
index=0
|
40 |
+
)
|
41 |
+
analyze_btn = st.button("Analyze")
|
|
|
|
|
|
|
42 |
|
43 |
+
# 主内容区
|
44 |
+
if analyze_btn:
|
45 |
+
models = load_models()
|
46 |
+
df = load_data()
|
47 |
|
48 |
+
with st.spinner("Generating recommendations..."):
|
49 |
+
# 获取风格示例
|
50 |
+
examples = df[df['style'] == style].sample(3)
|
51 |
+
|
52 |
+
# 分析对象和颜色
|
53 |
+
objects = []
|
54 |
+
colors = []
|
55 |
+
for img in examples['image']:
|
56 |
+
detected = models["detector"](img)
|
57 |
+
objects += [obj['label'] for obj in detected if obj['score'] > 0.8]
|
58 |
+
colors += get_colors(img)
|
59 |
+
|
60 |
+
# 生成建议
|
61 |
+
prompt = f"""Create {style} style decoration tips for Airbnb with:
|
62 |
+
- Key objects: {Counter(objects).most_common(3)}
|
63 |
+
- Color palette: {Counter(colors).most_common(3)}
|
64 |
+
Include: 3 essentials, 2 budget tips"""
|
65 |
+
|
66 |
+
advice = models["generator"](prompt, max_length=300)[0]['generated_text']
|
67 |
+
|
68 |
+
# 显示结果
|
69 |
+
col1, col2 = st.columns(2)
|
70 |
+
|
71 |
+
with col1:
|
72 |
+
st.subheader("Key Elements")
|
73 |
+
for obj, count in Counter(objects).most_common(3):
|
74 |
+
st.markdown(f"- {obj} (appears in {count} samples)")
|
75 |
+
|
76 |
+
st.subheader("Color Palette")
|
77 |
+
for color in Counter(colors).most_common(3):
|
78 |
+
st.markdown(f"<div style='background:{color[0]}; width:100%; height:30px'></div>",
|
79 |
+
unsafe_allow_html=True)
|
80 |
+
st.caption(color[0])
|
81 |
+
|
82 |
+
with col2:
|
83 |
+
st.subheader("Professional Advice")
|
84 |
+
st.write(advice)
|
85 |
+
|
86 |
+
st.subheader("Example Images")
|
87 |
+
st.image(examples['image'].tolist(), width=300)
|