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View Code? Open in Web Editor NEWAlgorithm Engineer Toolbox, for the purpose of quickly iterating new ideas
Algorithm Engineer Toolbox, for the purpose of quickly iterating new ideas
可以上传一份最新版本的baidu_image_search_demo.py吗
报错是这几行
url_upload_textbox = browser.find_element_by_css_selector('#app > div > div.page-banner > div.page-search > div > div > div.graph-search-left > input')
url_upload_textbox.send_keys(image_url)
# 识图一下
search_image_button = browser.find_element_by_css_selector('#app > div > div.page-banner > div.page-search > div > div > div.graph-search-center')
search_image_button.click()
好像百度识图页面换了,> div.page-banner > div.page-search > 这些不太一样,可以麻烦看看吗?
➜ keyframes_extract_tool python keyframes_extract_diff.py
/usr/bin/python
target video :pikachu.mp4
frame save directory: ./extract_result/
Using Local Maxima
1923 50
Traceback (most recent call last):
File "keyframes_extract_diff.py", line 195, in <module>
plt.locator_params(numticks=100)
File "/home/yopoint/.local/lib/python3.6/site-packages/matplotlib/pyplot.py", line 2744, in locator_params
return gca().locator_params(axis=axis, tight=tight, **kwargs)
File "/home/yopoint/.local/lib/python3.6/site-packages/matplotlib/axes/_base.py", line 3006, in locator_params
self.xaxis.get_major_locator().set_params(**kwargs)
File "/home/yopoint/.local/lib/python3.6/site-packages/matplotlib/ticker.py", line 2212, in set_params
f"set_params() got an unexpected keyword argument '{key}'")
TypeError: set_params() got an unexpected keyword argument 'numticks'
➜ keyframes_extract_tool
作者您好,我运行了您的对于视频关键帧提取的代码,对于一个7分钟的短视频,代码需要耗时3分钟才能提取完毕,所以这个是不是有点耗时啊?
You need to convert alpha as below to make it work with Tensorflow 2. Assuming alpha input as a list:
alpha = np.array(alpha).reshape(len(alpha), 1)
alpha = tf.convert_to_tensor(alpha, dtype=tf.float32)
Steve
I want to share an AI application platform called Dify that can help train text data for you.I hope this tool can be included in this warehouse, because it can also help people with the same needs.
The goal of Dify is to allow developers (even non-developers) to quickly build something useful based on a large language model, and ensure that it is visualized, operable, and improveable.
In other words, you can upload papers in PDF, Markdown, TXT and other text formats and let AI learn the content. After the application is published, it can interact with people based on the uploaded data.
I trained a dedicated chatbot and threw the product documentation of Tencent Cloud CODING DevOps into it, and the effect was good. That is to say, GPT can answer all questions related to its own company's products.
Robot experience address: https://udify.app/chat/F2Y4bKEWbuCb1FTC
Source document address: https://coding.net/help
Training platform: https://dify.ai/
My practice document (official account): https://mp.weixin.qq.com/s/WuFZ3FFcEwPNOcIKQQZsIA
Personal WeChat account: AdolfJobs
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