Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+from gtts import gTTS
+import io
+import os
+
+# function part
+# img2text
+def img2text(url):
+    image_to_text_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
+    text = image_to_text_model(url)[0]["generated_text"]
+    return text
+
+# text2story
+def text2story(text):
+    story_generator = pipeline("text-generation", model="Qwen/QwQ-32B")
+    story = story_generator(text, max_length=200, num_return_sequences=1)[0]["generated_text"]
+    return story
+
+# text2audio
+def text2audio(story_text):
+    # 创建 gTTS 对象
+    tts = gTTS(text=story_text, lang='en')
+    # 创建一个字节流对象用于存储音频数据
+    audio_file = io.BytesIO()
+    # 将音频数据写入字节流
+    tts.write_to_fp(audio_file)
+    # 将文件指针移到开头
+    audio_file.seek(0)
+    return audio_file
+
+st.set_page_config(page_title="Your Image to Audio Story",
+                   page_icon="🦜")
+st.header("Turn Your Image to Audio Story")
+uploaded_file = st.file_uploader("Select an Image...")
+
+if uploaded_file is not None:
+    # 保存上传的文件到临时文件
+    temp_file_path = "temp_image.jpg"
+    bytes_data = uploaded_file.getvalue()
+    with open(temp_file_path, "wb") as file:
+        file.write(bytes_data)
+    st.image(uploaded_file, caption="Uploaded Image",
+             use_column_width=True)
+
+    # Stage 1: Image to Text
+    st.text('Processing img2text...')
+    scenario = img2text(temp_file_path)
+    st.write(scenario)
+
+    # 删除临时文件
+    if os.path.exists(temp_file_path):
+        os.remove(temp_file_path)
+
+    # Stage 2: Text to Story
+    st.text('Generating a story...')
+    story = text2story(scenario)
+    st.write(story)
+
+    # Stage 3: Story to Audio data
+    st.text('Generating audio data...')
+    audio_data = text2audio(story)
+
+    # Play button
+    if st.button("Play Audio"):
+        st.audio(audio_data,
+                 format="audio/mpeg",
+                 start_time=0)