If you’ve been scrolling through social media lately, you’ve probably seen the explosion of Studio Ghibli-style images everywhere. These charming, anime-inspired portraits have taken the internet by storm, with everyone from celebrities to your next-door neighbor transforming their photos into magical Ghibli artwork. While ChatGPT Plus subscribers ($20/month) have been leading this trend, I’ve discovered several completely free alternatives that deliver similar results. Let me walk you through exactly how to create these enchanting images without spending a rupee.

What’s the Ghibli Style Image Trend All About?

Studio Ghibli is a renowned Japanese animation studio founded by Hayao Miyazaki, known for beloved films like “Spirited Away,” “My Neighbor Totoro,” and “Howl’s Moving Castle”12. Their distinctive artistic style features soft pastel colors, meticulous details, and a dreamy, whimsical quality that has captivated audiences worldwide.

The recent trend began when OpenAI rolled out its GPT-4o update, which included an enhanced image generator capable of transforming ordinary photos into Ghibli-inspired artwork14. While initially limited to paying subscribers, there are now ways for everyone to join the fun.

Free Methods to Create Ghibli-Style Images

1. Free Access to ChatGPT (Limited)

According to recent reports, ChatGPT allows free users to generate up to three Ghibli-style images before requiring a subscription10. To try this limited option:

1. Open the latest version of ChatGPT
2. Tap the three-dot icon on the prompt bar
3. Select the “Image” option
4. Provide a detailed prompt describing your desired Ghibli-style image1214

2. Using Gemini AI

Google’s Gemini AI offers a fantastic free alternative for creating Ghibli-style images:

1. Go to the Gemini AI platform and log in with your Google account
2. In the chat box, describe the image you want to create in detail
3. Submit your prompt and wait for the AI to generate your image
4. Download and share your creation10

This method works best when you provide specific details about what you want in your Ghibli-style image.

3. Transform Images with Grok

Grok, developed by xAI, has emerged as another excellent free option:

1. Visit the Grok website or app
2. Upload your image by clicking on the paper clip icon
3. Ask Grok to “Ghiblify” the image or “transform this into Studio Ghibli style”
4. Download your Ghibli-style creation when it’s ready1012

Users report that while Grok’s results might not match ChatGPT Plus’s precision, they’re more than adequate for personal use and social media sharing.

4. Third-Party AI Image Generators

Several other platforms can create Ghibli-style images without cost:

• Craiyon: A free AI image generator accepting text prompts
• Playground AI: Offers both text-to-image and image transformation features
• Deep AI: Provides style transfer capabilities that can mimic the Ghibli aesthetic14

For these platforms, try prompts like “Create an image in the style of Japanese hand-drawn animation showing [your description]” or upload an image and request a stylistic transformation.

Note that this limited access might not be available to all users yet, as the feature is still rolling out gradually.

Tips for Getting Better Results

No matter which platform you use, these tips will help improve your Ghibli-style transformations:

Be Specific in Your Prompts

Instead of simply requesting “Ghibli style,” try more descriptive prompts like:

• “Transform this image into a hand-drawn illustration with soft colors and detailed backgrounds inspired by Japanese animated films”
• “Convert this photo to resemble the artistic style seen in Miyazaki’s animated works”13

Work Around Copyright Restrictions

Many users have reported receiving content policy violation messages when directly mentioning “Studio Ghibli”711. Try these alternatives:

• “In the style of Hayao Miyazaki”
• “Japanese anime aesthetic with painterly backgrounds”
• “Dreamy animation style with pastel colors”13

Focus on Key Style Elements

For the most authentic Ghibli look, emphasize:

• Soft, muted color palettes
• Detailed natural elements (clouds, grass, trees)
• Warm, gentle facial expressions
• Whimsical, dreamlike qualities12

Troubleshooting Common Issues

If you encounter problems with generating Ghibli-style images, try these solutions:

Content Policy Restrictions

Some platforms restrict certain image types or subjects. Users have reported issues with animal photos in particular7. Try:

• Using human subjects instead of animals
• Modifying your prompt to avoid potential policy violations
• Describing the scene rather than uploading an image

“Copyright Violation” Errors

If you receive this message, rephrase your prompt to avoid direct mention of copyrighted properties13. For example:

• Instead of “Studio Ghibli style,” try “dreamy Japanese animation style”
• Instead of mentioning specific Ghibli films, describe the visual style you want

Ethical Considerations

While creating Ghibli-style images is fun, it’s worth noting that Miyazaki himself has expressed skepticism about AI’s role in animation12. When sharing your AI-generated artwork:

• Acknowledge they are AI-generated
• Use them for personal enjoyment rather than commercial purposes
• Be mindful of the ongoing discussions about AI and creative works

Final Thoughts

The Ghibli style image trend showcases how AI is making artistic styles more accessible to everyone. While ChatGPT Plus offers polished results, the free alternatives outlined here provide excellent options for joining this creative movement without spending money.

Whether you choose Gemini AI, Grok, or other free image generators, you can now transform your photos into magical Ghibli-inspired artwork that captures that special blend of wonder and nostalgia. Try these methods today and share your creations with friends – you might be surprised by how magical your ordinary photos can become!

As someone who actively participates in crypto airdrops, I’ve uncovered some of the most promising opportunities this year. Airdrops are not just about free tokens; they’re a gateway to exploring new blockchain projects and technologies. In this post, I’ll share the next set of airdrops you shouldn’t miss in 2024. These projects are making waves in the crypto space, and by joining them, you can earn rewards while supporting innovation.

1. DeNet: Decentralized Web Services

DeNet is redefining web hosting and data storage with its decentralized, secure, and cost-effective platform. By eliminating reliance on centralized cloud providers, DeNet empowers users to host websites and store files securely. Participants in the DeNet airdrop can receive free DNET tokens by joining their community on Discord, following their social media channels, and completing simple tasks.

• How to Participate: Sign up on the official DeNet website, complete tasks, and claim your free tokens.
• Why It’s Exciting: DeNet’s decentralized approach challenges traditional cloud giants, giving users control and reducing costs. Early adopters can benefit from being part of this transformative project.

2. AlphaOS: Blockchain Operating System

AlphaOS aims to create an operating system optimized for blockchain applications. This innovative platform offers enhanced security, seamless blockchain integration, and a developer-friendly environment. Early adopters who join the AlphaOS airdrop can secure exclusive rewards and early access to their ecosystem.

• How to Participate: Register on the AlphaOS platform and engage in promotional activities.
• Why It’s Exciting: As blockchain adoption grows, AlphaOS is positioning itself as the backbone for decentralized applications. Their airdrop rewards can provide a valuable stake in this emerging ecosystem.

3. Kaiser ZeroNode: Decentralized VPN Solution

Kaiser ZeroNode is revolutionizing online privacy with its decentralized VPN, offering users anonymity and data protection without relying on centralized servers. This project’s unique approach ensures that users retain control over their internet connections. Joining their airdrop program provides free tokens and early access to their beta platform.

• How to Participate: Follow Kaiser ZeroNode’s official social media accounts and join their Telegram group to complete tasks and earn tokens.
• Why It’s Exciting: Privacy is a growing concern, and Kaiser ZeroNode’s decentralized VPN is a game-changer for secure and anonymous browsing.

4. Bless: Blockchain-based Donation Platform

Bless leverages blockchain technology to create a transparent and efficient donation platform. By connecting donors directly with recipients, it ensures that every contribution is accounted for and maximized. Bless’s airdrop rewards participants with tokens for signing up, promoting the platform, and engaging in its community.

• How to Participate: Visit the Bless website, register, and share their mission on social media to claim your tokens.
• Why It’s Exciting: Bless’s mission to make donations transparent and impactful resonates with the values of blockchain technology. Being part of this initiative is both rewarding and meaningful.

5. OpenLoop: Decentralized Freelance Marketplace

OpenLoop aims to disrupt the freelancing industry by creating a decentralized platform where freelancers and clients can connect without hefty commissions. With built-in smart contracts ensuring fair payments and dispute resolution, OpenLoop is set to become a game-changer. Their airdrop offers free tokens for completing onboarding tasks.

• How to Participate: Sign up on the OpenLoop platform, complete your profile, and refer friends to earn tokens.
• Why It’s Exciting: Freelancers and clients can benefit from lower costs and greater transparency. OpenLoop’s vision aligns perfectly with the decentralized ethos.

Why Airdrops Matter to Me

Participating in airdrops has allowed me to discover and support emerging projects while earning tokens that often appreciate in value. It’s also a way to stay ahead in the fast-evolving crypto space. By engaging with these projects, I’ve not only gained financial rewards but also insights into groundbreaking technologies.

Tips to Maximize Airdrop Opportunities

1. Stay Informed: Follow official project channels on social media to get timely updates.
2. Use Secure Wallets: Ensure you’re using wallets compatible with the project’s blockchain.
3. Engage Actively: Many projects reward community engagement, so participate in discussions and activities.
4. Verify Information: Only follow official links to avoid scams.

Final Thoughts

These airdrops offer more than just free tokens; they provide a chance to be part of revolutionary projects shaping the future of blockchain technology. By joining these airdrops, you can diversify your crypto portfolio while supporting innovation. Don’t miss out—take the plunge and explore these opportunities today!

Sorting numbers in ascending order is one of the most basic operations in programming, often achieved using built-in functions like Python’s sort() or sorted(). However, solving this problem without using these helper functions can significantly improve your understanding of algorithms and how sorting actually works under the hood.

In this blog, we will explore how to implement an ascending order sorting algorithm in Python without using the sort() function. We’ll discuss various methods, including popular sorting algorithms like bubble sort, selection sort, and insertion sort. We’ll also delve into the time complexities and strengths of these algorithms, followed by a step-by-step explanation of how to implement them in Python.

Why Avoid the Sort Function?

While Python’s built-in sorting function is powerful and optimized, it’s important to understand the mechanics behind sorting algorithms for several reasons:

1. Learning Purpose: Understanding how sorting algorithms work is fundamental to improving your algorithmic thinking and problem-solving skills.
2. Customization: You might want to sort data based on specific criteria that the built-in sort can’t handle directly.
3. Algorithm Optimization: In some cases, you might want to use a different algorithm based on time complexity and space requirements.

Now, let’s get into various methods to achieve sorting in ascending order without using Python’s built-in sort() function.

1. Bubble Sort Algorithm

Bubble sort is one of the simplest sorting algorithms. It repeatedly steps through the list, compares adjacent elements, and swaps them if they are in the wrong order. This pass through the list is repeated until the list is sorted.

How Bubble Sort Works:

• In each pass, adjacent elements are compared.
• If the current element is greater than the next one, they are swapped.
• The largest element “bubbles up” to its correct position at the end of the list after each pass.

Time Complexity:

• Best case (already sorted): O(n)
• Worst case: O(n²)

Implementation in Python:

def bubble_sort(arr):
    n = len(arr)
    for i in range(n):
        # Flag to check if the list is already sorted
        swapped = False
        # Traverse the array from 0 to n-i-1
        # Last i elements are already sorted
        for j in range(0, n-i-1):
            # Swap if the element found is greater than the next element
            if arr[j] > arr[j+1]:
                arr[j], arr[j+1] = arr[j+1], arr[j]
                swapped = True
        # If no two elements were swapped in the inner loop, break
        if not swapped:
            break
    return arr

Example

array = [64, 34, 25, 12, 22, 11, 90]
sorted_array = bubble_sort(array)
print(f"Sorted array: {sorted_array}")

Output:

Sorted array: [11, 12, 22, 25, 34, 64, 90]

In this algorithm, we iterate through the list, compare pairs, and swap them if necessary. After each pass, the largest unsorted element moves to the end of the list. The algorithm stops early if no swaps are made during a pass, indicating that the list is already sorted.

2. Selection Sort Algorithm

Selection sort works by selecting the smallest (or largest, depending on sorting order) element from the unsorted portion of the list and swapping it with the first unsorted element. The process is repeated until the entire list is sorted.

How Selection Sort Works:

• Traverse the list and find the minimum element.
• Swap it with the first element.
• Move to the next element and repeat the process for the remaining unsorted portion.

Time Complexity:

• Best case: O(n²)
• Worst case: O(n²)

Implementation in Python:

def selection_sort(arr):
    n = len(arr)
    for i in range(n):
        # Assume the first element is the minimum
        min_idx = i
        # Traverse the rest of the array to find the minimum element
        for j in range(i+1, n):
            if arr[j] < arr[min_idx]:
                min_idx = j
        # Swap the found minimum element with the first unsorted element
        arr[i], arr[min_idx] = arr[min_idx], arr[i]
    return arr

Example

array = [29, 10, 14, 37, 14]
sorted_array = selection_sort(array)
print(f"Sorted array: {sorted_array}")

Output:

Sorted array: [10, 14, 14, 29, 37]

Selection sort is easy to understand and implement but isn’t very efficient for large lists due to its O(n²) time complexity. It performs well on small datasets but is rarely used in production.

3. Insertion Sort Algorithm

Insertion sort builds the sorted list one element at a time. It picks each element and inserts it into its correct position relative to the already sorted portion of the list.

How Insertion Sort Works:

• Start from the second element, assuming the first element is sorted.
• Compare the current element with the elements in the sorted portion.
• Shift all the larger elements in the sorted portion one position to the right.
• Insert the current element in its correct position.

Time Complexity:

• Best case (already sorted): O(n)
• Worst case: O(n²)

Implementation in Python:

def insertion_sort(arr):
    # Traverse from the second element (index 1) to the end
    for i in range(1, len(arr)):
        key = arr[i]
        # Move elements of arr[0..i-1], that are greater than key, to one position ahead
        j = i - 1
        while j >= 0 and key < arr[j]:
            arr[j + 1] = arr[j]
            j -= 1
        # Place key at its correct position
        arr[j + 1] = key
    return arr

Example

array = [12, 11, 13, 5, 6]
sorted_array = insertion_sort(array)
print(f"Sorted array: {sorted_array}")

Output:

Sorted array: [5, 6, 11, 12, 13]

Insertion sort is more efficient than bubble sort and selection sort for small datasets or nearly sorted data. It works well when the list is almost sorted, as it minimizes the number of shifts.

4. Merge Sort Algorithm

Merge sort is a divide-and-conquer algorithm that recursively divides the list into two halves until each half has one element, and then merges the halves back together in sorted order.

How Merge Sort Works:

• Recursively split the list into halves.
• Sort each half.
• Merge the two sorted halves.

Time Complexity:

• Best and worst case: O(n log n)

Implementation in Python:

def merge_sort(arr):
    if len(arr) > 1:
        # Find the middle of the array
        mid = len(arr) // 2
        # Split the array into two halves
        left_half = arr[:mid]
        right_half = arr[mid:]

        # Recursively sort both halves
        merge_sort(left_half)
        merge_sort(right_half)

        # Merge the sorted halves
        i = j = k = 0
        while i < len(left_half) and j < len(right_half):
            if left_half[i] < right_half[j]:
                arr[k] = left_half[i]
                i += 1
            else:
                arr[k] = right_half[j]
                j += 1
            k += 1

        # Copy the remaining elements of left_half
        while i < len(left_half):
            arr[k] = left_half[i]
            i += 1
            k += 1

        # Copy the remaining elements of right_half
        while j < len(right_half):
            arr[k] = right_half[j]
            j += 1
            k += 1
    return arr

Example

array = [38, 27, 43, 3, 9, 82, 10]
sorted_array = merge_sort(array)
print(f"Sorted array: {sorted_array}")

Output:

Sorted array: [3, 9, 10, 27, 38, 43, 82]

Merge sort has a better time complexity than bubble, selection, and insertion sorts. It is often used in situations where stability (preserving the order of equal elements) is important, but it requires additional memory space for merging, which makes it less space-efficient than other algorithms like quicksort.

5. Quick Sort Algorithm

Quick sort is another divide-and-conquer algorithm. It works by selecting a “pivot” element from the list and partitioning the other elements into two sublists—those less than the pivot and those greater than the pivot. The sublists are then recursively sorted.

How Quick Sort Works:

• Pick a pivot element.
• Partition the list into two sublists: elements less than the pivot and elements greater than the pivot.
• Recursively apply the same process to the sublists.

Time Complexity:

• Best case: O(n log n)
• Worst case (poor pivot selection): O(n²)

Implementation in Python:

def quick_sort(arr):
    if len(arr) <= 1:
        return arr
    else:
        pivot = arr[len(arr) // 2]


 left = [x for x in arr if x < pivot]
        middle = [x for x in arr if x == pivot]
        right = [x for x in arr if x > pivot]
        return quick_sort(left) + middle + quick_sort(right)

Example

array = [3, 6, 8, 10, 1, 2, 1]
sorted_array = quick_sort(array)
print(f"Sorted array: {sorted_array}")

Output:

Sorted array: [1, 1, 2, 3, 6, 8, 10]

Quick sort is one of the most efficient sorting algorithms in practice, with average time complexity of O(n log n). However, it can degrade to O(n²) in the worst case when the pivot selection is poor.

Conclusion

Sorting a list in ascending order without using Python’s built-in sort() function helps you understand the different sorting algorithms and their nuances. Each algorithm has its strengths and weaknesses, which are primarily determined by the dataset size and characteristics. For small datasets, bubble, insertion, or selection sorts might suffice, while for larger datasets, merge sort and quicksort are better suited.

Understanding these algorithms allows you to make informed choices when working with different types of data and teaches you how to write efficient code. By implementing these algorithms in Python, you also gain a deeper appreciation for the built-in sort() function and its underlying efficiency.