小编Nol*_*bus的帖子

我正在尝试将用 python 编写的 Streamlit 应用程序部署到 Heroku。我的整个目录是 4.73 MB，其中 4.68 MB 是我的 ML 模型。我的requirements.txt看起来像这样：

absl-py==0.9.0
altair==4.0.1
astor==0.8.1
attrs==19.3.0
backcall==0.1.0
base58==2.0.0
bleach==3.1.3
blinker==1.4
boto3==1.12.29
botocore==1.15.29
cachetools==4.0.0
certifi==2019.11.28
chardet==3.0.4
click==7.1.1
colorama==0.4.3
cycler==0.10.0
decorator==4.4.2
defusedxml==0.6.0
docutils==0.15.2
entrypoints==0.3
enum-compat==0.0.3
future==0.18.2
gast==0.2.2
google-auth==1.11.3
google-auth-oauthlib==0.4.1
google-pasta==0.2.0
grpcio==1.27.2
h5py==2.10.0
idna==2.9
importlib-metadata==1.5.2
ipykernel==5.2.0
ipython==7.13.0
ipython-genutils==0.2.0
ipywidgets==7.5.1
jedi==0.16.0
Jinja2==2.11.1
jmespath==0.9.5
joblib==0.14.1
jsonschema==3.2.0
jupyter-client==6.1.1
jupyter-core==4.6.3
Keras-Applications==1.0.8
Keras-Preprocessing==1.1.0
kiwisolver==1.1.0
Markdown==3.2.1
MarkupSafe==1.1.1
matplotlib==3.2.1
mistune==0.8.4
nbconvert==5.6.1
nbformat==5.0.4
notebook==6.0.3
numpy==1.18.2
oauthlib==3.1.0
opencv-python==4.2.0.32
opt-einsum==3.2.0
pandas==1.0.3
pandocfilters==1.4.2
parso==0.6.2
pathtools==0.1.2
pickleshare==0.7.5
Pillow==7.0.0
prometheus-client==0.7.1
prompt-toolkit==3.0.4
protobuf==3.11.3
pyasn1==0.4.8 …

我正在使用 TikTok 的官方 SDK ( https://developers.tiktok.com/doc/video-kit-ios-video-kit-with-swift ) 将我的应用中的视频分享到 TikTok。我使用的方法如下所示：

func openVideoShareMenu(fileUri: String) {
  let request = TikTokOpenSDKShareRequest()
        request.mediaType = TikTokOpenSDKShareMediaType.video
        var mediaLocalIdentifiers: [String] = []
        mediaLocalIdentifiers.append(fileUri)
        request.localIdentifiers = mediaLocalIdentifiers
        DispatchQueue.main.async {
          request.send(completionBlock: { response in
            print("Response from TikTok")
          })
        }
}

该字符串fileUri指向一个现有文件，如下所示/var/mobile/Containers/Data/Application/83EB0771-25A6-43A5-9F9F-B859D21DB795/Documents/exportvideo.mp4。执行此方法时发生的唯一事情是 TikTok 应用程序打开，显示加载动画，然后立即返回到我的应用程序。在日志中我可以看到以下输出：

realnote_app[25056:2173434] 8.8.0 - [Firebase/Analytics][I-ACS023001] Deep Link does not contain valid required params. URL params: {
    "error_code" = "-4";
    "error_string" = "Permissions denied";
    "from_platform" = tiktoksharesdk;
    "request_id" = "3BEA07B3-19EF-46F1-90B2-8E112748CEA8";
    "response_id" = "51CEF72B-D265-449C-929B-372F2401AA7C";
    "share_state" …

我正在尝试scikit-image使用 python 3.5 在我的 Windows 7 64 位机器上安装该软件包。安装scikit时，满足要求：

Requirement already satisfied: six>=1.7.3 in c:\users\x\appdata\local\programs\python\python35\lib\site-packages (from scikit-image)
Requirement already satisfied: networkx>=1.8 in c:\users\x\appdata\local\programs\python\python35\lib\site-packages (from scikit-image)
Requirement already satisfied: pillow>=2.1.0 in c:\users\x\appdata\local\programs\python\python35\lib\site-packages (from scikit-image)
Requirement already satisfied: PyWavelets>=0.4.0 in c:\users\x\appdata\local\programs\python\python35\lib\site-packages (from scikit-image)
Requirement already satisfied: decorator>=4.1.0 in c:\users\x\appdata\local\programs\python\python35\lib\site-packages (from networkx>=1.8->scikit-image)
Requirement already satisfied: numpy>=1.9.1 in c:\users\x\appdata\local\programs\python\python35\lib\site-packages (from PyWavelets>=0.4.0->scikit-image)

但最终，安装失败：

UnicodeDecodeError: 'charmap' codec can't decode byte 0x81 in position 114: character maps to <undefined>

    ----------------------------------------

  Failed building wheel for scikit-image
Command …

我有一个热图，其中包含一些值 ( model_prediction_i)。因为我想稍后在绘制之前旋转此热图，所以我必须使用plt.imsave. 然后，我的目标是，显示reference.jpg为图的背景，在其上绘图，X_test_i然后将热图也放置在该图上，这样我就可以看到背景、绘制的线和热图，它们的尺寸比背景小图片 -> 它只会遮挡一部分背景图片。作为reference.jpg： 这可能吗？

import numpy as np
from PIL import Image
import matplotlib.pyplot as plt

model_prediction_i = np.zeros((200,200))
model_prediction_i[160][160] = 1
model_prediction_i[160][161] = 1
model_prediction_i[160][162] = 1
model_prediction_i[160][163] = 1
model_prediction_i[160][164] = 1
model_prediction_i[160][165] = 1
model_prediction_i[160][166] = 1
model_prediction_i[160][167] = 1
model_prediction_i[160][168] = 1
model_prediction_i[160][169] = 1
model_prediction_i[160][170] = 1
model_prediction_i[160][171] = 1

plt.imsave('outfile.jpg', model_prediction_i, cmap='hot')
rotated_img = Image.open('outfile.jpg')
background = Image.open('reference.jpg')


X_test_i = np.zeros((5, 2)) …

我有两个双精度数组 a 和 b，想要计算它们之间的余弦相似度。我的代码如下所示：

double [][] target = new double [1][65000];
double [][] compare = new double [1][65000];

double dotProduct = dot(target[0], compare[0]);
double eucledianDist = norm2(target) * norm2(compare);
double output = dotProduct / eucledianDist;

private double norm2(double[][] a){
    double sum = 0;
    for (int i = 0; i < a[0].length; i++){
        sum = sum + a[0][i] * a[0][i];
    }
    return Math.sqrt(sum);
}

private double dot(double[] a, double [] b){
    double sum = 0;
    for(int i = 0; i < …