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ios – Major view’s border in my customized UIview class is on high of one other view


Screenshot of my subject

I’ve a problem the place the primary view’s border of a customized UIview class I’ve is occurring high of the rankbadgeview inside this tradition class. I am unable to for the lifetime of me work out why. I’ve tried bringing the rankbadgeview subview to the entrance together with the uilabel within it and nonetheless would not work. Can anyone assist me spot the problem?

class LeaderboardCircleView: UIView {
    non-public let mainLabel = UILabel()
    let rankBadgeView = UIView()
    non-public let rankLabel = UILabel()
    non-public let scoreLabel = UILabel()
    
    init(mainText: String, rankText: String, backgroundColor: UIColor, rating: Int) {
        tremendous.init(body: .zero)
        setupViews()
        configure(mainText: mainText, rankText: rankText, backgroundColor: backgroundColor, rating: rating)
    }
    
    required init?(coder: NSCoder) {
        fatalError("init(coder:) has not been carried out")
    }


    non-public func updateScoreLabelWith(rating: Int) {
        let trophyAttachment = NSTextAttachment()
        trophyAttachment.picture = UIImage(systemName: "trophy.fill")?.withTintColor(.systemYellow, renderingMode: .alwaysOriginal)
        trophyAttachment.bounds = CGRect(x: 0, y: -2, width: 16, peak: 16)
        
        let trophyString = NSAttributedString(attachment: trophyAttachment)
        let scoreString = NSAttributedString(string: " (rating) pts", attributes: [
            .font: AppStyle.shared.headerFont(size: 12),
            .foregroundColor: UIColor.darkGray
        ])
        
        let fullScoreText = NSMutableAttributedString()
        fullScoreText.append(trophyString)
        fullScoreText.append(scoreString)
        
        scoreLabel.attributedText = fullScoreText
    }

    
    non-public func setupViews() {
        layer.borderWidth = 2
        layer.borderColor = AppStyle.shared.primaryColor?.cgColor
        translatesAutoresizingMaskIntoConstraints = false
        clipsToBounds = false
        
        mainLabel.translatesAutoresizingMaskIntoConstraints = false
        mainLabel.textAlignment = .middle
        mainLabel.adjustsFontSizeToFitWidth = true
        mainLabel.minimumScaleFactor = 0.5
        mainLabel.numberOfLines = 2
        mainLabel.font = AppStyle.shared.headerFont(dimension: 18)
        mainLabel.textColor = .white
        addSubview(mainLabel)
        
        rankBadgeView.translatesAutoresizingMaskIntoConstraints = false
        rankBadgeView.clipsToBounds = true
        rankBadgeView.backgroundColor = AppStyle.shared.primaryColor
        rankBadgeView.layer.zPosition = 1  // Sends it behind the border

        addSubview(rankBadgeView)
        
        rankLabel.translatesAutoresizingMaskIntoConstraints = false
        rankLabel.textAlignment = .middle
        rankLabel.font = AppStyle.shared.headerFont(dimension: 12)
        rankLabel.textColor = .white
        rankBadgeView.addSubview(rankLabel)
        
        scoreLabel.translatesAutoresizingMaskIntoConstraints = false
        scoreLabel.textAlignment = .middle
        scoreLabel.adjustsFontSizeToFitWidth = true
        scoreLabel.minimumScaleFactor = 0.5
        scoreLabel.numberOfLines = 1
        addSubview(scoreLabel)
        
        NSLayoutConstraint.activate([
            mainLabel.leadingAnchor.constraint(equalTo: leadingAnchor, constant: 10),
            mainLabel.trailingAnchor.constraint(equalTo: trailingAnchor, constant: -10),
            mainLabel.centerXAnchor.constraint(equalTo: centerXAnchor),
            mainLabel.centerYAnchor.constraint(equalTo: centerYAnchor),
            
            rankBadgeView.centerXAnchor.constraint(equalTo: centerXAnchor),
            rankBadgeView.bottomAnchor.constraint(equalTo: bottomAnchor, constant: 12),
            rankBadgeView.widthAnchor.constraint(equalToConstant: 30),
            rankBadgeView.heightAnchor.constraint(equalToConstant: 30),
            
            rankLabel.centerXAnchor.constraint(equalTo: rankBadgeView.centerXAnchor),
            rankLabel.centerYAnchor.constraint(equalTo: rankBadgeView.centerYAnchor),
            
            scoreLabel.topAnchor.constraint(equalTo: rankBadgeView.bottomAnchor, constant: 4),
            scoreLabel.centerXAnchor.constraint(equalTo: centerXAnchor)
        ])
        
        bringSubviewToFront(rankBadgeView)
        rankBadgeView.bringSubviewToFront(scoreLabel)
    }
    
    non-public func configure(mainText: String, rankText: String, backgroundColor: UIColor, rating: Int) {
        mainLabel.textual content = mainText
        self.backgroundColor = backgroundColor
        rankLabel.textual content = rankText
        
        let trophyAttachment = NSTextAttachment()
        trophyAttachment.picture = UIImage(systemName: "trophy.fill")?.withTintColor(.systemYellow, renderingMode: .alwaysOriginal)
        trophyAttachment.bounds = CGRect(x: 0, y: -2, width: 16, peak: 16)
        
        let trophyString = NSAttributedString(attachment: trophyAttachment)
        let scoreString = NSAttributedString(string: " (rating) pts", attributes: [
            .font: AppStyle.shared.headerFont(size: 12),
            .foregroundColor: UIColor.darkGray
        ])
        
        let fullScoreText = NSMutableAttributedString()
        fullScoreText.append(trophyString)
        fullScoreText.append(scoreString)
        
        scoreLabel.attributedText = fullScoreText
    }
    
    override func layoutSubviews() {
        tremendous.layoutSubviews()
        
        layer.cornerRadius = bounds.width / 2
        rankBadgeView.layer.cornerRadius = rankBadgeView.bounds.width / 2
        
        layer.shadowColor = UIColor.black.cgColor
        layer.shadowOpacity = 0.2
        layer.shadowRadius = 6.0
        layer.shadowOffset = CGSize(width: 0, peak: 4)
        layer.masksToBounds = false
        
        rankBadgeView.layer.shadowColor = UIColor.black.cgColor
        rankBadgeView.layer.shadowOpacity = 0.2
        rankBadgeView.layer.shadowRadius = 4.0
        rankBadgeView.layer.shadowOffset = CGSize(width: 0, peak: 2)
        rankBadgeView.layer.masksToBounds = false
    }
    
    func replace(mainText: String, rankText: String, backgroundColor: UIColor, rating: Int) {
        configure(mainText: mainText, rankText: rankText, backgroundColor: backgroundColor, rating: rating)
    }
}

10 Finest AI Pre-Manufacturing Instruments for Filmmakers (April 2025)

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AI is remodeling how filmmakers deal with pre-production duties. From scriptwriting to storyboarding and scheduling, AI pre-production instruments for filmmakers are serving to to hurry up tedious processes and improve creativity. Historically, getting ready a movie or video challenge entails plenty of handbook effort – breaking down scripts, sketching storyboards, planning shoot schedules, and so forth. This may be time-consuming and error-prone. In at this time’s market, there’s an explosion of AI-driven software program geared toward fixing these issues.

Filmmakers now have entry to AI instruments that may routinely analyze scripts, generate idea artwork, and even create storyboards from textual content. The result’s a quicker workflow and the flexibility to visualise concepts a lot earlier within the course of. On this piece, we’ll discover among the finest AI pre-production instruments accessible.

Comparability Desk of Finest AI Pre-Manufacturing Instruments for Filmmakers

AI Software Finest For Worth Options
LTX Studio Full AI pre-production $35/mo All-in-one platform
Filmustage Computerized script breakdown & scheduling $39/mo AI identifies script components
Boords Storyboarding & animatics $49/mo AI storyboard generator with constant characters
Midjourney Idea artwork & visible moodboards $10/mo Photorealistic picture technology
ChatGPT Story ideation and scriptwriting assist $20/mo Pure language AI
Studiovity All-in-one script, storyboard, scheduling $24/mo Built-in suite (screenwriting, shot lists, name sheets)
Adobe Firefly Idea artwork enhancing & generative fill Inc. with Adobe CC AI picture technology/enhancing
Largo.ai Movie challenge evaluation & casting selections Customized Predictive analytics on scripts
Cuebric  Digital-production Use-case based mostly Generates layered 2.5-D plates
NolanAI All-in-one writing $40/mo AI Co-Pilot

*The usual month-to-month plans are used for pricing when relevant.

10 Finest AI Pre-Manufacturing Instruments for Filmmakers

LTX Studio is a holistic AI-powered filmmaking platform designed to take you from thought to storyboard to last edit in a single software. It’s particularly highly effective for pre-production: you may feed in a script or idea and LTX will routinely generate an in depth visible storyboard with AI-created photos and even video previews. This provides administrators and producers a technique to visualize scenes early, experiment with digicam angles, and refine the story earlier than capturing a single body.

The platform runs within the cloud (web-based), supporting collaboration in order that your group can co-create and iterate on the challenge collectively.

Past storyboards, LTX Studio gives instruments for enhancing and submit, making it a one-stop-shop. For pre-production, its standout characteristic is the AI storyboard generator and picture generator – you may describe a scene in textual content and it’ll create idea artwork or storyboard frames in your chosen fashion.

Execs and Cons

  • Covers ideation, storyboarding, and even enhancing in a single place.
  • Transforms scripts into storyboards routinely, saving tons of time.
  • You possibly can tweak artwork fashion, temper, characters – not simply generic output.
  • A broad characteristic set means it may be complicated for newcomers to study all instruments.
  • Being cloud-based, it wants a secure connection to make use of all options.

Who that is for: LTX Studio is right for filmmakers who need one built-in AI answer for pre-production.

Pricing (USD)

  • Free
  • Lite – $15/month
  • Customary – $35/month
  • Professional – $125/month
  • Enterprise – Customized

Go to LTX Studio →

Filmustage is an AI-powered pre-production assistant that tackles the mundane components of planning a movie. It excels at script breakdown and scheduling – duties sometimes accomplished by assistant administrators or manufacturing managers over days can now occur in minutes.

Utilizing pure language processing (NLP), Filmustage routinely scans your screenplay and identifies key components like characters, props, places, and VFX necessities. This breakdown is the muse for all of your planning paperwork.

As soon as the script components are tagged, Filmustage helps generate capturing schedules (it provides a digital stripboard) and even name sheets. It makes use of AI to kind scenes by optimum capturing order, counsel scheduling tweaks, and may auto-generate a synopsis or script evaluation highlighting potential dangers.

Execs and Cons

  • Turns a script into an inventory of scenes, solid, props, and so forth., in seconds.
  • Auto-generates a capturing schedule with scene order options, saving days of coordination.
  • Contains name sheet generator, VFX breakdowns, budgeting aids, and extra in a single platform.
  • Runs within the browser; offline use isn’t doable, which may be limiting on set or with out web.
  • Decrease-tier plans cap the variety of initiatives you may run with AI per thirty days.
  • The breakdown isn’t 100% excellent – you’ll nonetheless have to overview and proper occasional tagging errors.

Who that is for: Filmustage is a sensible software for producers, 1st ADs, and manufacturing managers.

Pricing (USD)

  • Free
  • Award-Successful Plan – $49/month
  • Wonderful Studio Plan (Most Fashionable) – $149/month
  • Enterprise Plan – Customized

Go to Filmustage →

Boords is a well-liked on-line storyboarding software program that now options an AI Storyboard Generator. It’s designed for administrators, editors, or anybody planning a video who could not have robust drawing expertise.

With Boords, you may enter a script or description of a scene, and the AI will create a sequence of storyboard panels full with photos and captions. This implies in a number of seconds, you get a tough visible define of your story reasonably than ranging from a clean web page.

One standout Boords characteristic is its Character Tips software, which solves a typical downside with AI picture technology: holding characters constant throughout a number of photographs. You possibly can outline a personality’s look as soon as, and Boords’ AI will ensure the identical character seems in each body (reasonably than altering look every time).

Execs and Cons

  • Generates storyboard panels from easy textual content prompts or script enter, no drawing wanted.
  • Distinctive AI characteristic to keep up the identical character designs throughout all frames.
  • Helps teamwork, versioning, and exports to PDFs or MP4 animatics for simple sharing.
  • The auto-generated artwork, whereas clear, has a sure fashion (e.g. easy drawings); complicated artwork kinds may require further tweaking.
  • To get the most effective photos, you could have to refine textual content prompts – there’s a little bit of trial and error concerned.
  • Full capabilities require a paid plan; the free model is proscribed within the variety of frames/initiatives.

Who that is for: Boords is sweet for filmmakers who wish to visualize their script rapidly or put collectively a storyboard for a pitch.

Pricing (USD)

  • Lite – $19/month
  • Customary – $49/month
  • Workflow – $99/month

Go to Boords →

Midjourney is a prime AI picture generator identified for its unimaginable skill to create detailed, imaginative visuals from textual content prompts. Whereas not constructed particularly for filmmakers, it has change into a go-to software for a lot of within the trade to supply idea artwork, temper boards, and design concepts throughout pre-production.

With Midjourney, you may describe a setting (“a futuristic cityscape at sundown” or “medieval fortress inside with candlelight”) and it’ll render a high-quality picture that matches that description. That is invaluable for manufacturing designers and administrators who wish to discover the feel and appear of their movie’s world.

For instance, you may generate idea artwork for a location to information your location scouting, or create character portraits to encourage costume and make-up design. Midjourney’s outputs are typically very polished – usually corresponding to skilled idea artwork – and may spark new concepts you hadn’t thought of.

Execs and Cons

  • Produces beautiful, detailed photos that may go for actual idea artwork or location pictures.
  • Nice for brainstorming visuals – it usually provides inventive particulars that may encourage your artistic course.
  • You possibly can request kinds (photorealistic, cartoon, noir, and so forth.) to match the aesthetic of your challenge.
  • Midjourney is a normal AI, so it received’t break down a script or know your shot record – it purely generates photos.
  • Crafting the precise textual content immediate is essential; anticipate to iterate descriptions to get the right picture.
  • There’s no limitless free use – after a trial, it requires a subscription and the associated fee can improve for those who want plenty of photos.

Who that is for: Midjourney is an glorious software for administrators, manufacturing designers, and artwork departments trying to rapidly produce idea imagery.

Pricing (USD)

  • Fundamental – $10/month
  • Customary – $30/month
  • Professional Plan – $60/month
  • Mega Plan – $120/month

Go to Midjourney →

ChatGPT is a widely known AI language mannequin, and it may be a strong writing assistant for filmmakers throughout pre-production. Whereas it’s not a specialised movie software, many creators use ChatGPT to assist with duties like story growth, scriptwriting, and analysis.

As an example, you may brainstorm plot concepts or “what if” eventualities with ChatGPT – it could actually generate doable storylines or counsel how a personality may react in a given state of affairs. Some screenwriters use it to beat author’s block: you may have ChatGPT draft a scene or suggest dialogue, then you definitely refine it in your individual voice.

Moreover, ChatGPT can analyze and summarize materials. You could possibly paste a synopsis of your story and ask for suggestions or ask the AI to search out any plot holes or unclear factors (it gives a sort of pseudo-“protection”). For factual analysis or concepts (like “record some distinctive penalties of time journey I might discover in a script”), ChatGPT is like an clever advisor.

Execs and Cons

  • Nice for brainstorming themes, plot factors, title concepts, and extra – the AI can produce many choices so that you can take into account.
  • Can draft scenes or dialogues in screenplay fashion if prompted, providing you with a tough materials to construct on.
  • Helps with fast analysis (historic context, scientific ideas for sci-fi, and so forth.) and summarizing prolonged textual content.
  • The output could also be generic or want important enhancing – it’s not going to supply final-quality script pages by itself.
  • It doesn’t really perceive emotion or subtext as a human author does, so artistic judgment remains to be on you.
  • Over-reliance could make your work really feel formulaic; finest used as a complement, not a alternative for human creativity.

Who that is for: For filmmakers who may not have a co-writer or writing room, ChatGPT provides a sounding board for concepts and a fast technique to hash out written supplies.

Pricing (USD)

  • Free
  • Plus – $20/month
  • Professional – $200/month
  • Crew – $30/consumer/month
  • Enterprise – Customized

Go to ChatGPT →

Studiovity is an all-in-one movie pre-production software program that mixes screenwriting, storyboarding, scheduling, and extra – and it bakes in AI to help you alongside the way in which. In Studiovity, you may write your screenplay (it has a contemporary script editor with index playing cards and beat boards), then use the AI Script Breakdown characteristic to routinely establish components in your script (characters, props, places, and so forth.)

After breakdown, Studiovity helps you create storyboards and shot lists (you may sketch or connect photos, and handle shot specs), generate capturing schedules and calendars, and even make name sheets.

The AI comes into play with what they name “Magic Scheduling” – basically utilizing the breakdown information to draft a capturing schedule for you – and refining dialogue or translating scripts immediately.

Execs and Cons

  • Handles writing, planning, and group collaboration multi function app – no have to juggle a number of software program.
  • Automates tedious breakdown duties and suggests a shoot schedule, saving you time in pre-pro.
  • Accessible on net, Android, iOS – your script and plans are at all times accessible and updated throughout units.
  • As a result of it does a lot, it could actually take some time to study all options (although the interface is trendy, as famous).
  • Studiovity is comparatively new; it will not be as polished in every characteristic as devoted single-purpose instruments.
  • The AI options (breakdown, and so forth.) want web and their server processing – offline, you’d be restricted to the handbook use of the app.

Who that is for: Studiovity is finest suited to low-budget and indie filmmakers or scholar filmmakers who will profit from an built-in pre-production hub.

Pricing (USD)

  • Screenplay Writing – $2.50/month
  • Video Pre-Manufacturing – $24/month
  • Enterprise – Customized

Go to Studiovity →

Adobe Firefly is Adobe’s suite of generative AI instruments, now built-in into Inventive Cloud apps like Photoshop. For filmmakers in pre-production, Firefly’s Generative Fill and text-to-image options may be extraordinarily useful within the artwork division and storyboarding section.

When you’ve got a location picture or an idea picture, you need to use Generative Fill (in Photoshop Beta) so as to add or take away components with a easy immediate. For instance, you could possibly take a photograph of a road and ask Firefly to “add futuristic neon indicators” or “change to nighttime with rain.” The AI will manipulate the picture to match, offering a fast idea of set alterations or totally different temper lighting.

Firefly may also generate photos from scratch based mostly on prompts, much like Midjourney (although targeted on extra commercially protected outputs). Inside Illustrator or Photoshop, you may generate idea artwork for a prop or a emblem for a fictional firm in your movie.

The benefit of Firefly for filmmakers is that it’s constructed into the instruments designers already use, and outputs are available as editable layers.

Execs and Cons

  • Generative Fill helps you to prolong or modify photos immediately in Photoshop with pure outcomes.
  • Rapidly check out totally different set designs, costume variations, or lighting situations with out elaborate handbook portray.
  • In the event you already subscribe to Adobe Inventive Cloud, Firefly options are included, so no further subscription.
  • It’s a normal artistic software – doesn’t do scripts, schedules, and so forth. It strictly helps with visuals.
  • You want Photoshop Beta (or future variations) to make use of Generative Fill successfully. In the event you’re not conversant in Adobe instruments, there’s a studying curve.
  • Some desired capabilities may nonetheless be in beta and never 100% excellent on each try.

Who that is for: Adobe Firefly is a boon for manufacturing designers, administrators, and storyboard artists who wish to play with visible concepts swiftly.

Pricing (USD)

  • Customary – $9.99/month
  • Firefly Professional – $29.99 month
  • Firefly Premium – $199.99/month
  • Pricing for college kids, academics, and groups exists.

Go to Adobe Firefly→

Largo.ai is kind of totally different from the opposite instruments on this record – as a substitute of making content material, it analyzes and predicts. Aimed toward producers and filmmakers making high-level selections, Largo.ai is an AI-driven analytics platform for movie growth. You feed it your screenplay (or synopsis, or perhaps a tough reduce of the movie), and Largo’s algorithms will consider components like style, theme, emotion arcs, and examine them with an unlimited database of movie information.

The platform then gives predictions on viewers enchantment, distribution potential, and even casting selections that might enhance the movie’s success.

Key options embrace Emotional Depth Evaluation – Largo charts the emotional beats of your story (pleasure, disappointment, worry, and so forth.) throughout the script to see if it aligns with profitable patterns or if there are lulls. It can also do casting evaluation: for instance, you may question which actor’s presence may improve a movie’s field workplace potential for a given style, or see in case your casting selections align with what attracts the target market.

Execs and Cons

  • Provides an goal take a look at your script’s strengths and weaknesses (e.g., pacing of feelings) that you just may overlook.
  • Can counsel what viewers demographic your challenge skews in the direction of and easy methods to improve enchantment (like recommending a sure actor identified to draw that demo).
  • By seeing comparative evaluation with previous profitable movies, you may make knowledgeable selections (particularly helpful when pitching to traders or studios with concrete numbers).
  • Largo.ai received’t make your film higher artistically – actually, purely following its options might homogenize creativity (so use with stability).
  • It’s a high-end software, doubtless priced for manufacturing firms; solo creators may discover it costly (usually structured as yearly licenses or per-project charges).
  • The predictions are extra correct in case you have a reasonably developed script or movie reduce. In very early idea levels, it’s much less helpful.

Who that is for: Largo.ai is finest suited to producers, government producers, or administrators who need to gauge the business viability of their challenge.

Pricing (USD)

  • Yearly Licensing Price – $12,000

Go to Largo.ai →

Cuebric is a generative-AI platform constructed particularly for virtual-production and LED-stage filmmaking. In seconds it turns a textual content immediate (or an uploaded idea picture) right into a high-resolution, layered 2.5-D atmosphere that’s able to load on an LED wall—letting administrators “go from idea to digicam in minutes.”

Beneath the hood, Cuebric bundles 5 key workflows: (1) picture technology at as much as 16 Ok; (2) AI-driven segmentation that auto-layers foreground, mid-ground, and background; (3) in-painting and enhancing instruments to scrub plates; (4) superscaling for crystal-clear LED playback; and (5) one-click export to Unreal Engine or Disguise. The result’s a film-ready backdrop you may iterate on stay throughout tech scouts or capturing.

Execs and Cons

  • Creates 2.5-D plates with right parallax for LED levels.
  • Technology, segmentation, in-painting, enhancing, and export in a single software.
  • Cuts atmosphere construct time from weeks to minutes, enabling speedy artistic iteration.
  • Finest worth is on initiatives capturing with LED volumes or heavy VFX.
  • 2.5-D export and Disguise integration sit in upper-tier plans.
  • Wants a stable connection and cloud compute; offline use is proscribed.

Who that is for: Cuebric is ideal for administrators, manufacturing designers, and VFX groups embracing digital manufacturing.

Pricing (USD)

  • Use-case based mostly. Contact for precise numbers.

Go to Cuebric →

NolanAI is an all-in-one, AI-driven filmmaking suite that takes you from clean web page to pre-production paperwork in a single cloud workspace. Its “AI Co-Pilot Editor” suggests plot factors, flags clichés, and codecs your screenplay routinely, whereas the one-click Script Breakdown tags each prop, character, location, and VFX cue in underneath a minute.

From there, NolanAI generates beat sheets, shot lists, and even pitch-deck slides—successfully appearing as a digital writers’ room and manufacturing workplace rolled into one.

Past writing, NolanAI’s analytics engine compares your script to a database of produced movies, providing plot-hole detection, pacing graphs, and audience-appeal forecasts that may strengthen your story earlier than you lock the draft. Actual-time collaboration lets a number of writers or producers bounce in concurrently, and computerized cloud sync retains each revision protected.

Execs and Cons

  • Dwell options, formatting, and cliché alerts pace up writing.
  • One click on to generate components lists, saving hours of handbook tagging.
  • Plot-hole detection and viewers forecasts give data-driven perception earlier than you pitch.
  • Requires an web connection; no desktop-offline mode but.
  • Solutions can miss nuance, so human rewriting remains to be important.
  • Superior analytics and limitless initiatives sit in paid tiers.

Who that is for: It’s superb for writer-directors and indie producers who crave AI pace with out sacrificing collaboration.

Pricing (USD)

  • Free
  • Creator – $40/month
  • Professional – $100/month

Go to NolanAI →

How one can Select the Proper AI Pre-Manufacturing Software

With so many AI instruments now within the filmmaker’s toolbox, choosing the proper ones comes right down to your particular wants and the scope of your challenge. Listed below are a number of sensible tricks to information your choice:

  • Determine Your Pre-Manufacturing Ache Factors: Begin by pinpointing which duties eat up essentially the most time or which expertise you lack. In the event you’re a writer-director who can’t draw, an AI storyboarding software (like Boords or LTX Studio) can be transformative. When you’ve got hassle with scheduling and group, a breakdown/scheduling AI (Filmustage or Studiovity) might be your finest buddy.
  • Take into account Your Funds and Scale: Some AI instruments are free or have free tiers, whereas others are premium. An indie brief movie group may get by fully on free variations and trials, whereas a characteristic movie in growth could justify investing in a software.
  • Assess Ease of Integration: You’ll need instruments that play properly together with your present workflow. In case your group already makes use of Photoshop closely, Adobe Firefly is a pure add-on.
  • Stability AI with Human Contact: Lastly, keep in mind these instruments are assistants, not magicians. Use them to enhance your expertise, not substitute them. A great rule of thumb is: if the AI saves you 50% of the time on a process, use that further time to refine and add private creativity to the output.

By evaluating your wants and testing choices, you’ll assemble a collection of AI instruments that successfully turns into your digital manufacturing group in pre-production – doing the heavy lifting of drudge work and permitting you to give attention to the artistic coronary heart of your challenge.

FAQ (AI Pre-Manufacturing Instruments)

1. How can AI enhance the accuracy of movie budgets?

AI analyzes historic price information and real-time quotes to forecast line-item bills with tighter variance.

2. What are the principle challenges of utilizing AI in movie pre-production

Knowledge high quality, artistic management, and group adoption—poor inputs or resistance can restrict AI’s effectiveness.

3. How does AI help within the creation of movie storyboards?

It converts script textual content into draft photos, sustaining shot order and character consistency in seconds.

4. Can AI-generated scripts keep the identical high quality as human-written ones?

They supply stable construction and concepts, however nonetheless want human rewriting to realize nuanced, standout storytelling.

5. How does AI assist in scheduling and managing movie shoots?

AI auto-builds stripboards and optimizes scene order by solid, location, and daylight to chop down setup time.

Flutter iOS Construct Failed on Simulator (Xcode 16.3): Unsupported possibility ‘-G’ regardless of Podfile modifications


I’m encountering a difficulty when attempting to run my Flutter software on the iOS simulator (iPhone 15 Professional Max, iOS 17.5). The construct course of fails with the next error:

Error (Xcode): unsupported possibility ‘-G’ for goal ‘x86_64-apple-ios15.0-simulator’

Couldn’t construct the appliance for the simulator.
Error launching software on iPhone 15 Professional Max.
I’m utilizing Flutter 3.29.2 (steady channel) and Xcode model 16.3. I’m additionally utilizing Firebase SDK model $FirebaseSDKVersion = ‘10.25.0’.

Right here is the total content material of my ios/Podfile:

Ruby

platform :ios, '15.0'
$FirebaseSDKVersion = '10.25.0'

# Configuration
ENV['COCOAPODS_DISABLE_STATS'] = 'true'
use_frameworks! :linkage => :static
use_modular_headers!

mission 'Runner', {
  'Debug' => :debug,
  'Profile' => :launch,
  'Launch' => :launch,
}

def flutter_root
  generated_xcode_build_settings_path = File.expand_path(File.be a part of('..', 'Flutter', 'Generated.xcconfig'), __FILE__)
  except File.exist?(generated_xcode_build_settings_path)
    increase "#{generated_xcode_build_settings_path} should exist. When you're working pod set up manually, make sure that flutter pub get is executed first"
  finish

  File.foreach(generated_xcode_build_settings_path) do |line|
    matches = line.match(/FLUTTER_ROOT=(.*)/)
    return matches[1].strip}. Attempt deleting Generated.xcconfig, then run flutter pub get"
finish

require File.expand_path(File.be a part of('packages', 'flutter_tools', 'bin', 'podhelper'), flutter_root)

flutter_ios_podfile_setup

goal 'Runner' do
  flutter_install_all_ios_pods File.dirname(File.realpath(__FILE__))

  # Firebase pods
  pod 'Firebase/Core', :modular_headers => true
  pod 'Firebase/Database', :modular_headers => true
  pod 'Firebase/Auth', :modular_headers => true
  pod 'Firebase/Messaging', :modular_headers => true
  pod 'FirebaseFirestore', :modular_headers => true
  pod 'GoogleUtilities', :modular_headers => true
finish

post_install do |installer|
  installer.pods_project.targets.every do |goal|
    flutter_additional_ios_build_settings(goal)

    goal.build_configurations.every do |config|
      config.build_settings['IPHONEOS_DEPLOYMENT_TARGET'] = '15.0'
      config.build_settings['ENABLE_BITCODE'] = 'NO'
      config.build_settings['CLANG_ALLOW_NON_MODULAR_INCLUDES_IN_FRAMEWORK_MODULES'] = 'YES'
      config.build_settings['ENABLE_MODULE_VERIFIER'] = 'NO'
      config.build_settings['ENABLE_USER_SCRIPT_SANDBOXING'] = 'NO'

      # Try and take away the problematic flag
      if config.build_settings['OTHER_CFLAGS']
        config.build_settings['OTHER_CFLAGS'].gsub!(/-G/, '')
      finish

      if config.build_settings['OTHER_LDFLAGS']
        config.build_settings['OTHER_LDFLAGS'].gsub!(/-G/, '')
      finish

      # Cleanup xcconfig information for Xcode 16.3 (try)
      if config.base_configuration_reference
        xcconfig_path = config.base_configuration_reference.real_path
        xcconfig = File.learn(xcconfig_path)
        xcconfig_mod = xcconfig.gsub(/DT_TOOLCHAIN_DIR/, "TOOLCHAIN_DIR")
        xcconfig_mod = xcconfig_mod.gsub(/-Gs*/, '') # Take away -G with trailing whitespace
        xcconfig_mod = xcconfig_mod.gsub(/s+-G($|s+)/, ' ') # Take away -G with main whitespace
        File.open(xcconfig_path, "w") file
      finish

      # Examine and cleanup different construct settings (try)
      ['OTHER_CFLAGS', 'OTHER_CPLUSPLUSFLAGS', 'OTHER_LDFLAGS', 'OTHER_SWIFT_FLAGS'].every do |setting|
        if config.build_settings[setting]
          if config.build_settings[setting].is_a?(String)
            config.build_settings[setting] = config.build_settings[setting].gsub(/-Gs*/, '')
          elsif config.build_settings[setting].is_a?(Array)
            config.build_settings[setting] = config.build_settings[setting].reject  flag == '-G' 
          finish
        finish
      finish
    finish
  finish

  installer.pods_project.build_configurations.every do |config|
    config.build_settings['CLANG_ALLOW_NON_MODULAR_INCLUDES_IN_FRAMEWORK_MODULES'] = 'YES'
    config.build_settings['EXCLUDED_ARCHS[sdk=iphonesimulator*]'] = 'arm64'
  finish
finish

I’ve tried a number of steps together with deleting Pods, Podfile.lock, DerivedData, working flutter clear, flutter pub get, and numerous pod set up variations. I additionally obtained a warning from CocoaPods concerning the bottom configuration:

[!] CocoaPods didn’t set the bottom configuration of your mission as a result of your mission already has a customized config set. To ensure that CocoaPods integration to work in any respect, please both set the bottom configurations of the goal Runner to Goal Help Information/Pods-Runner/Pods-Runner.profile.xcconfig or embrace the Goal Help Information/Pods-Runner/Pods-Runner.profile.xcconfig in your construct configuration (Flutter/Launch.xcconfig).
Curiously, I’ve tried so as to add logic within the post_install hook of the Podfile to explicitly take away the -G flag from numerous construct settings and even tried to change the xcconfig information straight, however the identical error persists.

Does anybody have perception into why this -G flag may nonetheless be inflicting points regardless of my makes an attempt to take away it within the Podfile? Are there different configurations in Xcode or Flutter that is perhaps introducing this flag? How can I resolve the “unsupported possibility ‘-G'” error on Xcode 16.3 for the iOS simulator on this Flutter mission?

Thanks in your help.

ios – glog 0.3.5 – Flipper-Glog 0.3.6 Construct Failure on macOS 15.4.1 and Xcode 16.3 with React Native


After updating to macOS 15.4.1 and Xcode 16.3, my React Native iOS construct is failing throughout pod set up. The precise error happens with Flipper-Glog, the place it is making an attempt to put in model 0.3.6 as a substitute of the beforehand working 0.3.5.

Putting in Flipper-Glog 0.3.6
[!] /bin/bash -c 
set -e
#!/bin/bash
# Copyright (c) Fb, Inc. and its associates.
#
# This supply code is licensed below the MIT license discovered within the
# LICENSE file within the root listing of this supply tree.

set -e

PLATFORM_NAME="${PLATFORM_NAME:-iphoneos}"
CURRENT_ARCH="${CURRENT_ARCH}"

if [ -z "$CURRENT_ARCH" ] || [ "$CURRENT_ARCH" == "undefined_arch" ]; then
    # Xcode 10 beta units CURRENT_ARCH to "undefined_arch", this results in incorrect linker arg.
    # it is higher to depend on platform title as fallback as a result of structure differs between simulator and machine

    if [[ "$PLATFORM_NAME" == *"simulator"* ]]; then
        CURRENT_ARCH="x86_64"
    else
        CURRENT_ARCH="armv7"
    fi
fi

export CC="$(xcrun -find -sdk $PLATFORM_NAME cc) -arch $CURRENT_ARCH -isysroot $(xcrun -sdk $PLATFORM_NAME --show-sdk-path)"
export CXX="$CC"

# Take away automake symlink if it exists
if [ -h "test-driver" ]; then
    rm test-driver
fi

./configure --host arm-apple-darwin

# Repair construct for tvOS
cat << EOF >> src/config.h
/* Add in so we've Apple Goal Conditionals */
#ifdef __APPLE__
#embrace 
#embrace 
#endif
/* Particular configuration for AppleTVOS */
#if TARGET_OS_TV
#undef HAVE_SYSCALL_H
#undef HAVE_SYS_SYSCALL_H
#undef OS_MACOSX
#endif
/* Particular configuration for ucontext */
#undef HAVE_UCONTEXT_H
#undef PC_FROM_UCONTEXT
#if outlined(__x86_64__)
#outline PC_FROM_UCONTEXT uc_mcontext->__ss.__rip
#elif outlined(__i386__)
#outline PC_FROM_UCONTEXT uc_mcontext->__ss.__eip
#endif
EOF

# Put together exported header embrace
EXPORTED_INCLUDE_DIR="exported/glog"
mkdir -p exported/glog
cp -f src/glog/log_severity.h "$EXPORTED_INCLUDE_DIR/"
cp -f src/glog/logging.h "$EXPORTED_INCLUDE_DIR/"
cp -f src/glog/raw_logging.h "$EXPORTED_INCLUDE_DIR/"
cp -f src/glog/stl_logging.h "$EXPORTED_INCLUDE_DIR/"
cp -f src/glog/vlog_is_on.h "$EXPORTED_INCLUDE_DIR/"

checking for a BSD-compatible set up... /usr/bin/set up -c
checking whether or not construct atmosphere is sane... sure
checking for arm-apple-darwin-strip... no
checking for strip... strip
checking for a thread-safe mkdir -p... ./install-sh -c -d
checking for gawk... no
checking for mawk... no
checking for nawk... no
checking for awk... awk
checking whether or not make units $(MAKE)... sure
checking whether or not make helps nested variables... sure
checking for arm-apple-darwin-gcc... /Functions/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/cc -arch armv7 -isysroot /Functions/Xcode.app/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS18.4.sdk
checking whether or not the C compiler works... no
/Customers/testuser/Library/Caches/CocoaPods/Pods/Launch/Flipper-Glog/0.3.6-1dfd6/lacking: Unknown `--is-lightweight' choice
Attempt `/Customers/testuser/Library/Caches/CocoaPods/Pods/Launch/Flipper-Glog/0.3.6-1dfd6/lacking --help' for extra info
configure: WARNING: 'lacking' script is simply too outdated or lacking
configure: error: in `/Customers/testuser/Library/Caches/CocoaPods/Pods/Launch/Flipper-Glog/0.3.6-1dfd6':
configure: error: C compiler can not create executables
See `config.log' for extra particulars

Atmosphere

  • macOS: 15.4.1
  • Xcode: 16.3
  • React Native challenge
  • Present Podfile configuration:
use_flipper!({ 'Flipper-Folly' => '2.5.3', 'Flipper' => '0.87.0', 'Flipper-RSocket' => '1.3.1' })

What I’ve Tried

  • Cleansing the construct folder
  • Eradicating Pods listing and Podfile.lock
  • Pod deintegrate and pod cache clear
  • Explicitly specifying Flipper-Glog model

Query

  1. What is the appropriate configuration for Flipper and its dependencies (particularly Flipper-Glog) for macOS 15.4.1 and Xcode 16.3?
  2. Is there a recognized compatibility difficulty with these variations?
  3. What is the really useful answer to repair these compilation errors?

Scientists Uncover 3 Hotspots of Lethal Rising Illness within the US – NanoApps Medical – Official web site


Virginia Tech researchers found six new rodent carriers of hantavirus and recognized U.S. hotspots, highlighting the virus’s adaptability and the impression of local weather and ecology on its unfold.

Hantavirus lately drew public consideration following reviews that it was the reason for demise for Betsy Arakawa, spouse of actor Gene Hackman. Regardless of the headlines, the virus stays comparatively unfamiliar to many, past its recognized affiliation with rodents.

Researchers at Virginia Tech have deepened scientific understanding of this doubtlessly lethal virus by learning its rodent hosts throughout North America. Utilizing knowledge from the Nationwide Science Basis, the crew recognized three main hotspots of hantavirus exercise in wildlife: Virginia, Colorado, and Texas. Additionally they documented 15 rodent species carrying the virus, six of which had not beforehand been acknowledged as hosts.

The findings have been printed within the journal Ecosphere.

A Virus With Pandemic Potential

“This undertaking is well timed as a result of hantavirus is taken into account an rising illness of pandemic potential with signs that resemble extreme COVID-19 infections,” stated Paanwaris Paansri, a Ph.D. pupil within the Division of Fish and Wildlife Conservation and co-author of the examine.

Hantaviruses are a household of viruses which have been recognized in areas all around the globe and may attain mortality charges much like different illnesses of excessive concern, equivalent to nipah and Ebola. In Asia, hemorrhagic fever with renal syndrome is attributable to the Hantaan virus, in Europe that syndrome is attributable to the Dobrava-Belgrade virus, and in North and South America, hantavirus pulmonary syndrome is attributable to Sin Nombre virus and Andes virus — all hantaviruses. Sin Nombre virus was first found in New Mexico in 1993.

Deer Mouse
The commonest service of the hantavirus in North America is the deer mouse. Credit score: Picture courtesy of David M. Gascoigne

Little is thought in regards to the ecology of hantaviruses in wildlife besides that the pathogen is unfold to people by inhalation of aerosolized excreta, urine, or saliva from asymptomatic rodent hosts, and it may be deadly in people.

The Virginia Tech crew used knowledge from the Nationwide Science Basis’s Nationwide Ecological Observatory Community program to achieve a greater understanding of hantavirus circulation in its sylvatic cycle — the pathogen’s life cycle in wildlife — by inspecting the environmental influences and geographical distribution of the rodent hosts. This system collected and examined 14,004 blood samples from 49 species at 45 discipline websites throughout the USA from 2014-19.

New Hosts, New Insights

“In North America, Peromyscus maniculatus, the deer mouse, is the commonest service however our examine additionally revealed that different rodent species have the next prevalence of hantavirus, which adjustments the present paradigm in hantavirus circulation in wildlife,” stated Paansri, whose mentor Affiliate Professor Luis E. Escobar, led the examine and is an affiliate with the Fralin Life Sciences Institute. “This new info is anticipated to assist us perceive the place and when hantavirus is almost definitely to happen, which is essential for predicting outbreaks and informing public well being officers.”

The invention of six new rodent species of hantavirus hosts is critical. A few of these newly found hosts inhabit areas the place conventional hosts, such because the deer mouse or the white-footed mouse (Peromyscus leucopus), are absent, which means they could possibly be potential reservoirs of the virus in new or neglected areas.

“This expands our understanding of the essential biology of the virus and reveals that the virus is extra adaptable than beforehand believed,” Paansri stated. “This has direct implications for surveillance methods and danger assessments and might help clarify some instances of hantavirus in people the place the primary reservoir is absent or uncommon.”

Along with increasing the recognized host species, the researchers have been capable of acquire a greater understanding of seasonal developments and results of seasonal climate shifts. For instance, hotter winters and elevated precipitation can improve rodent populations and drier situations can facilitate the era of contaminated mud containing particulates from rodent excrement and saliva, rising the danger of transmission to people.

The Position of Local weather Change

“Local weather change could cause inhabitants will increase or distributional shifts of rodents, altering the epidemiology of hantavirus,” Paansri stated. “These fluctuations can result in extra frequent rodent-human interactions and improve the possibility of spillover. We discovered some proof that rodent demography and hantavirus prevalence could be predicted months prematurely.”

The precise variety of human instances of hantavirus infections is basically unknown, based on Paansri, as a result of many infections stay silent, which means the contaminated particular person might not develop any signs or the signs might mirror different illnesses, such because the frequent chilly or influenza.

The researchers plan to additional discover the extent to which climatic variations affect hantavirus transmission in wildlife and in people.

“We consider that many classes realized from this examine could be generalized to different wildlife illnesses, contemplating that their distribution is international,” Paansri stated.

Reference: “Hantavirus in rodents in the USA: Temporal and spatial developments and report of recent hosts” by Francisca Astorga, Abdelghafar Alkishe, Paanwaris Paansri, Gabriel Mantilla and Luis E. Escobar, 16 March 2025, Ecosphere.
DOI: 10.1002/ecs2.70209