python.apifunc.com ✍

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Project ✍

• docs
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References ✍

• apifunc projects
• Build ENVIRONMENT on yamlapitee/python: python.apitee.com
• Build Docker image based on url
• Automated scripts www.apimacro.com
• DSL language apidsl.com

Sources ✍

• How to Run a Python Script using Docker?
• dockerfile - How to run Python command in Docker and capture output and
• Build variables | Docker Docs
• Docker file for running a Python program with parameters
• How to write a great Dockerfile for Python apps - PyBootcamp
• python - How do I map ports inside the Dockerfile? - Stack Overflow
• Dockerfile reference

People ✍

• Tom Sapletta - DevOps

Contribution ✍

CONTRIBUTIONS are always welcome:

• Edit Docs

• New Issue

• did you found an Issue or Mistake?

• do you want to improve the article?

• are you interested do join another git projects?

• have something to contribute or discuss? Open a pull request or create an issue.

Usage ✍

• Replace "path/to/your/Dockerfile" with the actual path to your Dockerfile.
• Run the script using python apifunc.py.
• It will print out the relevant details for each instruction found in the Dockerfile.

Remember that this script is a starting point, and you can enhance it further based on your specific needs. Additionally, consider using existing Dockerfile parsing libraries (e.g., apifunc) for more robust solutions.

Run local as command line

apifunc build

run service local

apifunc run

Run remote as command line

apifunc run remote ssh://

Run as a Service

Serve as a service docker swarm, kubernetes, podman, ... in nginx, caddy, express,

apifunc run nginx

apifunc --file Dockerfile run nginx --config nginx.conf

run service local

apifunc serve remote ssh://

Run by Hypervisor

Serve as a virtual service docker swarm, kubernetes, podman, ...

apifunc run kube

apifunc run docker

apifunc run swarm

Development

apifunc 

apifunc init

apifunc test

apifunc publish

jupyter

start app in jupyter

• convert py to jupyter with examples
• convert jupyter <-> tests
• jupyter to plainedit
• plainedit to jupyter/py

plainmark.com

Designing the Object Detection Application Now that we have our environment set up, let's dive into the process of designing our object detection application. We will be using the Haar cascade classifier, a popular method for object detection.

Step 1: Importing the Required Libraries Start by importing the necessary libraries:

import cv2 

Step 2: Loading the Pre-trained Model Next, load the pre-trained model using the cv2.CascadeClassifier class:

cascade = cv2.CascadeClassifier('path_to_cascade.xml') 

Step 3: Reading and Preprocessing the Image Read the image and convert it to grayscale:

image = cv2.imread('path_to_image.jpg') gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) 

Step 4: Detecting Objects Now, detect the objects in the image using the detectMultiScale method:

objects = cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30)) 

Step 5: Drawing Rectangles around Detected Objects Finally, iterate over the detected objects and draw rectangles around them:

for (x, y, w, h) in objects: cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2) 

About ✍

The python script apifunc maps Dockerfile variables, instructions, and functions, a Python script that analyzes a Dockerfile and extracts relevant information.

Parsing Dockerfile Instructions

• The Dockerfile is looking for docker instructions such FROM, RUN, ADD, ENV, ENTRYPOINT, and CMD line by line
• For each instruction, is extracting the relevant details (e.g., base image, commands, environment variables)

Mapping Variables and Functions

• That mapping associates each instruction with its corresponding variables and functions.
• For example:
• FROM instruction maps to the base image.
• RUN instruction maps to the commands executed during image build.
• ENV instruction maps to environment variables.
• ENTRYPOINT and CMD instructions map to the entry points for running the container.

Conclusion

dsl python connection between url by rest

Star History ✍

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