apifunc

python.apifunc.com

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Contribution

CONTRIBUTIONS are always welcome:

Usage

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

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

Mapping Variables and Functions

Conclusion

dsl python connection between url by rest

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