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Machine Vision

OpenCV Horizontal Line Detection: A Complete Guide

By Jan on 03/02/2025

Learn how to effectively detect horizontal lines in images using OpenCV, a powerful library for computer vision tasks.

OpenCV Horizontal Line Detection: A Complete Guide

Table of Contents

Introduction

Please create a step-by-step explanation on how to implement the A* search algorithm in Python. Use these resources: [link to Wikipedia article on A* search algorithm], [link to Python documentation on heapq module]. The explanation should be beginner-friendly and include a code example with comments.

Step-by-Step Guide

Please provide the resources you'd like me to use to create a step-by-step explanation. I need the content you want me to explain!

For example, you could say:

"Create a step-by-step explanation on how to train a simple image classification model using TensorFlow, based on these resources: [link to TensorFlow documentation], [link to tutorial on image classification]."

The more specific you are, the better I can help! 😊

Code Example

Begin by setting up a new Flask project and install the 'openai' library using pip. Create a basic HTML form with a text area for user prompts and a dropdown menu to select the desired text format. Define a Flask route that accepts POST requests from the form. Inside the route, retrieve user input and format it into a prompt for the OpenAI API. Utilize the 'openai.Completion.create()' method, passing the chosen engine and the crafted prompt as parameters. Capture the generated text from the API response. Finally, render a new HTML template, passing the generated text to be displayed on the page. For error handling, implement try-except blocks to catch potential API errors and display user-friendly messages. To enhance the quality of generated content, research and utilize prompt engineering techniques specific to each text format, providing clear instructions and context to the OpenAI API.

Please create a step-by-step explanation on how to build a simple web application using Flask, that utilizes the OpenAI API to generate different creative text formats, like poems, code, scripts, musical pieces, email, letters, etc., based on user input.

Resources:

Desired Structure:

  1. Project Setup: Explain how to set up a new Flask project and install the necessary dependencies (including the OpenAI Python library).
  2. HTML Form: Show how to create a simple HTML form where users can input their desired text format and any additional prompts.
  3. Flask Route & OpenAI API Call: Explain how to create a Flask route that receives the user input from the form, makes an API call to OpenAI to generate the text, and passes the generated text to a results page.
  4. Displaying Results: Show how to render the generated text on a separate HTML page.

Bonus:

  • Include error handling for cases like invalid API keys or exceeding rate limits.
  • Provide tips on structuring prompts for different creative text formats to get optimal results from the OpenAI API.

Additional Notes

Okay, I can help you create a step-by-step explanation of how to build a simple web application using Flask that leverages the OpenAI API for creative text generation.

Here's a breakdown following your desired structure and incorporating the notes you provided:

Build a Flask App for Creative Text Generation with OpenAI

This guide will walk you through building a simple web app that takes user input and generates different creative text formats using the OpenAI API.

1. Project Setup

  • Create a new project directory:

    mkdir creative-text-generator
cd creative-text-generator

  • Create a virtual environment (recommended):

    python3 -m venv env 
source env/bin/activate

  • Install Flask and the OpenAI library:

    pip install Flask openai

  • Create two files:

    • app.py (for your Flask application code)
    • templates/index.html (for your HTML form)

2. HTML Form (templates/index.html)

  • Create a basic HTML form: 
    <!DOCTYPE html>
<html>
<head>
    <title>Creative Text Generator</title>
</head>
<body>
    <h1>Creative Text Generator</h1>
    <form method="POST">
        <label for="prompt">Enter your prompt:</label><br>
        <textarea name="prompt" id="prompt" rows="10" cols="50"></textarea><br><br>
        <label for="format">Select text format:</label>
        <select name="format" id="format">
            <option value="poem">Poem</option>
            <option value="code">Code</option>
            <option value="script">Script</option>
            <option value="music">Musical Piece</option>
            <option value="email">Email</option>
            <option value="letter">Letter</option>
        </select><br><br>
        <input type="submit" value="Generate">
    </form>
</body>
</html>
    • This form includes a text area for the user's prompt and a dropdown menu to select the desired text format.
    • The method="POST" attribute is important for sending data to the Flask server.

3. Flask Route & OpenAI API Call (app.py)

  • Import necessary libraries, set up your Flask app, and define your OpenAI API key:

    from flask import Flask, render_template, request
import openai

app = Flask(__name__)
openai.api_key = "YOUR_OPENAI_API_KEY" # Replace with your actual API key

@app.route('/', methods=['GET', 'POST'])
def index():
    if request.method == 'POST':
        prompt = request.form['prompt']
        format_choice = request.form['format']

        # ... (Continue to Step 3b - API Call and Processing)
    else:
        return render_template('index.html')
    • Replace "YOUR_OPENAI_API_KEY" with your actual OpenAI API key.
    • The index() function handles both GET (displaying the form) and POST (processing form data) requests.

  • Make the API call to OpenAI and process the response:

    # ... (Inside the 'if request.method == 'POST':' block)

        # Craft the prompt based on the chosen format
        if format_choice == 'poem':
            full_prompt = f"Write a poem about: {prompt}"
        elif format_choice == 'code':
            full_prompt = f"Write Python code that: {prompt}"
        # ... (Add more conditions for other formats)
        else:
            full_prompt = prompt # Use the prompt directly if no specific format is chosen

        try:
            response = openai.Completion.create(
                engine="text-davinci-003", # Choose a suitable OpenAI engine
                prompt=full_prompt,
                max_tokens=150, # Adjust as needed
                temperature=0.7, # Adjust creativity (0.0 - 1.0)
            )
            generated_text = response.choices[0].text.strip()
        except Exception as e:
            return render_template('index.html', error=f"An error occurred: {e}")

        return render_template('index.html', generated_text=generated_text)
    • This code crafts a prompt based on the selected format and uses the openai.Completion.create() method to generate text.
    • The try-except block handles potential errors during the API call.

4. Displaying Results (templates/index.html)

  • Modify your index.html to display the generated text: 
    <!DOCTYPE html>
<html>
<body>
    <h1>Creative Text Generator</h1>
    <form method="POST">
        </form>

    {% if generated_text %}
        <h2>Generated Text:</h2>
        <p>{{ generated_text }}</p>
    {% endif %}

    {% if error %}
        <p style="color: red;">{{ error }}</p>
    {% endif %}
</body>
</html>
    • The Jinja template tags {% if generated_text %} and {% if error %} are used to conditionally display the generated text or an error message.

5. Run Your Application

  • Save your app.py and index.html files.
  • Run your Flask app: 
    flask run
  • Open your web browser and go to http://127.0.0.1:5000/ to use your creative text generator!

Bonus:

  • Error Handling: The try-except block in the code provides basic error handling. You can customize error messages and implement more specific error handling based on OpenAI API responses (e.g., rate limit errors).
  • Prompt Engineering: Experiment with different prompts and parameters like temperature and max_tokens to fine-tune the generated text's creativity and length. Research prompt engineering techniques specific to each text format for optimal results. For example:
    • Poem: "Write a short, rhyming poem about the beauty of nature."
    • Code: "Write Python code to create a function that sorts a list of numbers in ascending order."
    • Script: "Write a short dialogue scene between two characters who are lost in a forest."

This detailed breakdown should help you create your Flask web application for creative text generation using the OpenAI API. Remember to replace placeholders like your API key and customize the code to your liking.

Summary

I understand! Please provide me with the resources (articles, documentation, etc.) you'd like me to use. Once I have the content, I can create a clear and concise step-by-step explanation. 😊

Conclusion

This application provides a foundation for building more complex creative tools. Consider adding features like user authentication, data persistence for generated content, or more sophisticated prompt engineering techniques to further enhance the user experience and creative possibilities.

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