first push
Browse files- .streamlit/config.toml +2 -0
- app.py +236 -0
- model/banner.png +0 -0
- model/zha2024_6.h5 +3 -0
- requirements.txt +2 -0
.streamlit/config.toml
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[theme]
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base="dark"
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app.py
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import PIL.Image
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import numpy as np
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import os,re,pytz,time
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import streamlit as st
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from datetime import datetime
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import google.generativeai as genai
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import streamlit.components.v1 as components
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from tensorflow.keras.models import load_model
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from tensorflow.keras.preprocessing import image
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UTC_8 = pytz.timezone('Asia/Shanghai')
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#Load the model
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my_model = load_model("model/zha2024_5-83.38.h5")
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target_size = (300, 300)
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class_labels = {0: '炭黑组', 1: '正常发挥', 2: '炫彩组', 3: '糊糊组', 4: '炸组日常', 5: '凡尔赛',6: '非食物'}
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predicted_class=''
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#Set up the Gemini model and API key
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#https://cloud.google.com/vertex-ai/docs/generative-ai/model-reference/gemini?hl=zh-cn
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MY_KEY= os.environ.get("GOOGLE_API_KEY")
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genai.configure(api_key=MY_KEY)
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gemini_model = genai.GenerativeModel('gemini-pro-vision')
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neutral=os.environ.get("sys_info_0")
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toxic=os.environ.get("sys_info_1")
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heartfelt=os.environ.get("sys_info_2")
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chilly_list=os.environ.get("X").split(",")
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default_prompt=''
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generation_config = {
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"temperature": 0.99,
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"top_p": 1,
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"top_k": 40,
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"max_output_tokens": 2048,
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"candidate_count":1
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}
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safety_settings = [
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{
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"category": "HARM_CATEGORY_HARASSMENT",
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"threshold": "BLOCK_NONE"
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},
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{
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"category": "HARM_CATEGORY_HATE_SPEECH",
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"threshold": "BLOCK_NONE"
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},
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{
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"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
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"threshold": "BLOCK_NONE"
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},
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{
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"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
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"threshold": "BLOCK_NONE"
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}
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]
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#fuctions
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def preprocess_image(img_path):
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img = image.load_img(img_path, target_size=target_size)
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img_array = image.img_to_array(img)
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img_array = np.expand_dims(img_array, axis=0)
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return img_array
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def chilly_words_killer(text,words_list):
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for word in words_list:
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pattern = re.compile(re.escape(word), re.IGNORECASE)
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text = pattern.sub("**😮", text)
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return text
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def get_critic_info(review_style):
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if review_style == '默认':
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default_prompt = neutral
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critic_name = 'SavorBalancer'
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avatar = '👩🍳'
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elif review_style == '毒舌👾':
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default_prompt = toxic
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critic_name = 'SpicyCritique'
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avatar = '😈'
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elif review_style == '暖心🍀':
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default_prompt = heartfelt
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critic_name = 'GentleGourmet'
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avatar = '🤗'
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else:
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raise ValueError(f'Invalid review style: {review_style}')
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return default_prompt, critic_name, avatar
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def img_score(img_raw_path):
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global predicted_class
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img_array = preprocess_image(img_raw_path)
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predictions = my_model.predict(img_array)
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predicted_class_index = np.argmax(predictions, axis=-1)
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predicted_class = class_labels[predicted_class_index[0]]
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class_probabilities = {label: prob for label, prob in zip(class_labels.values(), predictions[0])}
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score={k: round(v * 100, 2) for k, v in class_probabilities.items()}
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high_score_float=predictions[0,(predicted_class_index[0])]
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high_score=round(high_score_float*100,2)
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return score,high_score
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def score_desc(score):
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if score > 90:
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return "这妥妥的属于"
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elif score >= 70 and score <= 90:
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return "这大概率属于"
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elif score >= 40 and score <= 70:
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return "这可能属于"
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else:
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return "我猜这属于"
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def review_waiting(_class, critic_name):
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if _class == '非食物':
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return '图里面好像没有食物吧❓'
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elif critic_name == 'SavorBalancer':
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return '🍴品尝中,正在构思点评'
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elif critic_name == 'SpicyCritique':
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return '不要催啦,我这不正在吃吗💢'
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elif critic_name == 'GentleGourmet':
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return '正在为你种彩虹🌈'
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def gemini_bot(default_prompt,img_raw_path,_class):
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img = PIL.Image.open(img_raw_path)
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model = gemini_model
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klass="当前食物类型是:"+_class
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prompt=klass+default_prompt
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response = model.generate_content([prompt, img],
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stream=False,
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safety_settings=safety_settings,
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generation_config=generation_config)
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response.resolve()
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response_text=f'''{response.text}'''
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final_response=chilly_words_killer(response_text,chilly_list)
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return final_response
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def review():
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if predicted_class is not None:
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with st.spinner(review_waiting(predicted_class, critic_name)):
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print(f"{datetime.now(UTC_8).strftime('%m-%d %H:%M:%S')}--Start Reviewing")
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final_response = gemini_bot(default_prompt, img_raw_path, predicted_class)
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with st.chat_message(critic_name, avatar=avatar):
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st.write(final_response)
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st.button("再次点评", key="1")
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print(f"{datetime.now(UTC_8).strftime('%m-%d %H:%M:%S')}--Complete\n💣💣💣")
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info('#edfde2','#78817a','🆗点评完毕,内容有AI生成,仅供娱乐',55)
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def info(bg_color,font_color,text,height):
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html=f'''<html><style>
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body {{
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margin: 0;
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padding: 0;
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color: #3b4740;
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background-color: transparent;
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}}
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.container {{
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max-width: 100%;
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margin: 0 auto;
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padding: 20px;
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font-size: 15px;
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color:{font_color}
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display: flex;
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justify-content: space-between;
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align-items: center;
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background-color: #f8e9a000;
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padding: 15px;
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border-radius: 10px;
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line-height: 1.6;
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border: #fde2e4 0px solid;
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background-color:{bg_color} ;
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}}
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</style><body><div class="container">
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{text}
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</body></html>'''
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components.html(html,height=height)
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#Streamlit UI
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#Guide: https://docs.streamlit.io/library/api-reference
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#st.header("🧨ZhazuEvaluator")
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#st.subheader('', divider='rainbow')
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st.image('https://cdnjson.com/images/2024/01/30/banner7f1835c564c9b79c.png')
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# Upload an image
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bg_color='#e1f1fa'
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border_font_color='#78817a'
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css=f'''<style>
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[data-testid="stFileUploadDropzone"]{{background-color:{bg_color};color:{border_font_color}}}
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[data-testid="baseButton-secondary"]{{background-color:{bg_color};border:1px {border_font_color} solid;color:{border_font_color}}}
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[data-testid="baseButton-secondary"]>div[data-testid="stMarkdownContainer"] {{border: none;}}
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div[data-testid="stFileDropzoneInstructions"]>div>span::after {{
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content:"✨来上传一张你的得意之作,PC可直接拖放上传";
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visibility:visible;
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display:block;
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}}
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</style>'''
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st.markdown(css,unsafe_allow_html=True)
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img_raw_path = st.file_uploader("", type=['png', 'jpg', 'jpeg','webp'])
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col1, col2 = st.columns(2)
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my_image = ""
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if not img_raw_path is None:
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my_image = img_raw_path.read()
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my_image = PIL.Image.open(img_raw_path)
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print(f"{datetime.now(UTC_8).strftime('%m-%d %H:%M:%S')}--IMG uploaded")
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with col1:
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st.image(my_image, caption='✅图片已上传', width=350)
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# Predict the class of the image
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if my_image:
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with st.spinner('💥正在打分中...'):
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print(f"{datetime.now(UTC_8).strftime('%m-%d %H:%M:%S')}--Start Classification")
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score,high_score=img_score(img_raw_path)
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with col2:
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st.bar_chart(score, color='#fdd3de',width=412)
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score_noti=f"📝{score_desc(high_score)}{predicted_class}➡️得分:{high_score}"
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info('#edfde2','#78817a',score_noti,55)
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review_style= st.radio(
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"请选择点评文字风格",
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["默认", "毒舌👾", "暖心🍀"],
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index=0, horizontal=True
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)
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default_prompt, critic_name, avatar=get_critic_info(review_style)
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#review
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if my_image:
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review()
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announcements='''注意事项\n
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1.上传的图片有一定概率不会被识别,可能出现点评完全和图片无关的情况,特别是非食物图片\n
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2.如果AI开始说车轱辘话,不断重复某个句式,内容也相关性不大,请重新点评。\n
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3.毒舌点评可能会出现轻微冒犯用语,请不要放在心上。
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'''
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st.warning(announcements)
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left_blank, centre,last_blank = st.columns([3.4,2,3])
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with centre:
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st.image("https://visitor-badge.laobi.icu/badge?page_id=Ailyth/z2024&left_text=MyDearVisitors&left_color=pink&right_color=Paleturquoise")
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model/banner.png
ADDED
![]() |
model/zha2024_6.h5
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:43b983819c030871eeae11ed79816b599402ccc2fc8d7d03dadc6a85c8539e52
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size 135402752
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requirements.txt
ADDED
@@ -0,0 +1,2 @@
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google.generativeai
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tensorflow
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