I85PREP
⌘ K
Cloudinary Media Developer study materials
Cloudinary Media Developer study resources

Cloudinary Media Developer practice questions

One question at a time. Build your Cloudinary Media Developer understanding.

First 50 of 190 questions. Each one lists the choices, the correct answer, and an explanation. The checker at the top of this page saves progress in this browser when it is available.

Continue in the practice tool above to load more questions, 50 at a time.

Question 1Cloudinary ingestion, identifiers and asset lifecycle

An application uses a difficult-to-guess Cloudinary public identifier for a sensitive photograph. Which conclusion follows about authorization?

  1. The identifier automatically expires when the browser closes
  2. The identifier guarantees that only the uploader can view every derivative
  3. The identifier addresses the asset but does not by itself establish a complete access policy Correct answer.
  4. The identifier replaces the need for supported delivery-type controls

Explanation

A public identifier is an addressing component rather than a universal authorization or expiry mechanism. Sensitive delivery needs the actual supported access configuration and its original/derived behavior.

Question 2Cloudinary ingestion, identifiers and asset lifecycle

A code review labels Cloudinary’s documented sorted-parameter-plus-secret SHA authentication procedure as HMAC. What should the reviewer do?

  1. Hash only the API key because it is already an identifier
  2. Use the exact official SDK/algorithm and distinguish secret-appended hashing from HMAC Correct answer.
  3. Replace the procedure with any HMAC implementation without checking compatibility
  4. Move the API secret to the browser so it can inspect the algorithm

Explanation

The service’s documented signature procedure must match exactly. A secret-appended hash and an HMAC construction are different algorithms; using another construction arbitrarily can produce invalid authentication.

Question 3Cloudinary ingestion, identifiers and asset lifecycle

An incoming transformation deliberately downsizes the stored source. The team later wants the discarded source detail for a large zoom view. What should have been reviewed?

  1. Only the CDN hostname because it recreates removed detail
  2. Only the tag spelling because tags encode image pixels
  3. The incoming transformation’s source-lifecycle effect and retention of an appropriate original Correct answer.
  4. Whether the filename contains enough random characters

Explanation

Incoming processing can alter the stored source available for later derivatives. Review source retention and intended future uses before discarding detail; delivery parameters cannot recreate guaranteed original information.

Question 4Cloudinary ingestion, identifiers and asset lifecycle

A supported asynchronous eager-processing workflow returns an accepted job reference. The required derivative is still pending. What should the application infer?

  1. The asset must have been deleted because processing is asynchronous
  2. The application may safely publish any guessed derivative URL as verified
  3. The workflow was accepted, but derivative readiness needs completion evidence Correct answer.
  4. Every derivative is ready because a reference exists

Explanation

Accepted asynchronous work and a ready derivative are different states. Follow the supported completion/status or verified notification workflow before promising that the required representation is available.

Question 5Cloudinary ingestion, identifiers and asset lifecycle

An asset has the tag confidential. The application has not configured restricted delivery. Which statement is correct?

  1. The tag describes metadata and does not automatically enforce access restriction Correct answer.
  2. The tag changes the image dimensions to zero
  3. The tag revokes every previously issued delivery URL
  4. The tag automatically encrypts the original and every derivative

Explanation

Tags can support organization and workflows, but a label alone is not a delivery access policy. Apply the actual supported authorization and lifecycle controls for the intended content.

Question 6Image/video transformations, geometry and visual intent

A product-card design explicitly needs a 400-by 300 pixel filled box and automatic selection of an interesting region. Which Cloudinary concept combination addresses both decisions?

  1. A fill crop plus an appropriate supported automatic-gravity qualifier Correct answer.
  2. Automatic format selection alone defines the box and subject
  3. A public identifier plus an upload timestamp defines the crop
  4. A fill crop alone guarantees automatic subject detection

Explanation

Fill mode addresses the requested geometry and cropping, while a supported automatic-gravity qualifier addresses region selection. Representative outputs still need visual verification.

Question 7Image/video transformations, geometry and visual intent

A supplied proportional-fit exercise starts with a 300-by 200 pixel image and fits it inside 100-by 100 without cropping or upscaling. Ignoring final integer rounding, what dimensions result?

  1. 100 by 66.67 pixels Correct answer.
  2. 66.67 by 100 pixels
  3. 150 by 100 pixels
  4. 100 by 100 pixels

Explanation

The limiting scale is 100/300, or one third. Applying that same factor to the 200 pixel height gives 66.67 pixels, preserving the supplied aspect ratio without a crop.

Question 8Image/video transformations, geometry and visual intent

A transformation chain resizes an asset before applying a visual effect. A colleague reverses the steps and assumes the output must be identical. What is the appropriate review?

  1. Ignore layer boundaries because they never affect the base image
  2. Evaluate the actual sequence because transformations can be order-dependent Correct answer.
  3. Treat every chain as an unordered set of effects
  4. Compare only the length of the URL string

Explanation

The output of one transformation can become input to the next, so changing sequence can change the result. Check actual layer scope and representative output rather than URL appearance.

Question 9Image/video transformations, geometry and visual intent

A named transformation definition changes. Existing users still request a previously cached derived URL. What should the rollout review consider?

  1. Only the original asset’s tag list
  2. The definition, derived-cache behavior and versioned/invalidation strategy together Correct answer.
  3. Whether the browser window has a different title
  4. Only the name’s spelling because every cached object changes immediately

Explanation

Named transformations centralize relevant definitions, but previously generated/cached outputs have their own lifecycle. Verify the actual versioning/invalidation and representative delivered results before claiming universal immediate change.

Question 10Image/video transformations, geometry and visual intent

A requirement says the video output must be 720 pixels wide while preserving aspect ratio. What should the reviewer avoid conflating with that requirement?

  1. The common 720p label describing a vertical video format Correct answer.
  2. A supplied explicit horizontal pixel measurement
  3. The need to retain the input aspect-ratio relationship
  4. The distinction between scaling and a cropping operation

Explanation

A stated 720 pixel width is a horizontal measurement, while the common 720p label refers to a vertical video format. Keep units, intended geometry and aspect-ratio behavior explicit.

Question 11Image/video transformations, geometry and visual intent

A format conversion preserves smaller file size but removes transparency needed by the design. Which review criterion was missing?

  1. Required alpha/visual behavior together with size and supported format handling Correct answer.
  2. Only whether the public identifier was short
  3. Only whether the upload used a timestamp
  4. Only whether a tag was present

Explanation

Media optimization must preserve required visual and functional properties as well as transfer efficiency. Verify actual alpha handling and output against the design, rather than treat smaller size as sufficient.

Question 12Cloudinary delivery, formats and responsive media

A browser advertises AVIF support, but the supported automatic-format workflow returns another eligible format. What is the sound conclusion?

  1. The image must be delivered at original dimensions
  2. The account’s API secret must be placed in the URL to force negotiation
  3. Accept-header capability alone does not prove that AVIF must be selected for every asset and setting Correct answer.
  4. Automatic format has failed whenever AVIF is not returned

Explanation

Automatic format selection considers its actual supported content/client/configuration conditions. A supported format capability does not by itself mandate one output for every asset, and dimensions remain another decision.

Question 13Cloudinary delivery, formats and responsive media

An automatic-width integration expects client hints, but the tested browser does not send the needed hint. What should the design address?

  1. Supported fallback or explicit responsive candidates based on the actual layout Correct answer.
  2. Assume every browser sends all hints and ignore the test
  3. Replace all image alt text with the desired width
  4. Encode the API secret in the image width parameter

Explanation

Responsive delivery depends on actual supported inputs. Provide a documented fallback or explicit candidates and validate representative browser behavior instead of promising that every hint is always available.

Question 14Cloudinary delivery, formats and responsive media

An overwritten media asset has an invalidation request in progress, while a browser still displays an older cached image. What is a plausible explanation?

  1. The browser proves the original overwrite could not have occurred
  2. Every cache must be cleared instantaneously by every invalidation request
  3. The old image proves all upload signatures are invalid
  4. Asset replacement and invalidation propagation/browser caching are separate lifecycle conditions Correct answer.

Explanation

Replacing an origin asset and removing every cached representation are different operations. Propagation and browser/intermediary caches can explain stale display without disproving the recorded asset update.

Question 15Cloudinary delivery, formats and responsive media

A deployment emits new content-hashed image URLs, but old cached pages still reference the previous URLs. Which transition plan is most defensible?

  1. Retain the required old resources for the supported transition while publishing the new immutable/versioned resources Correct answer.
  2. Reuse the old URL for unrelated bytes without checking cache behavior
  3. Delete every old resource immediately because hashes prevent all stale HTML
  4. Change the page title and assume old references disappear

Explanation

Versioned URLs separate representations, but existing pages can still reference old resources. Retain required versions during the supported transition and verify actual HTML/cache lifecycle before cleanup.

Question 16Media access, restricted sources and processing safety

A browser upload form currently embeds the account API secret in its JavaScript bundle. Which correction addresses that credential exposure?

  1. Change every image filename but keep the same exposed secret
  2. Move secret-bearing authorization to a trusted backend and provide only the intended bounded client authorization Correct answer.
  3. Rename the JavaScript variable while leaving its value in the bundle
  4. Put the secret in an HTML data attribute instead

Explanation

Client-delivered code and attributes can expose values to the recipient. Keep secret-bearing authorization on a trusted backend, then review and rotate any compromised credential through the authorized process.

Question 17Media access, restricted sources and processing safety

A developer promises that an ordinary signed Cloudinary delivery URL expires because upload signatures use timestamps. What is the defensible response?

  1. Accept the promise because every signature in the platform has the same lifetime
  2. Replace the public identifier with a longer string and call that expiration
  3. Remove the timestamp from uploads to shorten delivery access
  4. Verify the specific delivery access/lifetime mechanism; upload-signature semantics do not prove delivery-URL expiry Correct answer.

Explanation

Signing behavior is operation-specific. An ordinary delivery signature does not universally inherit an upload-signature lifetime, so the supported viewing-lifetime mechanism requires actual verification.

Question 18Media access, restricted sources and processing safety

A webhook claims that a media-processing operation completed and asks the application to publish its result. Which control is most appropriate?

  1. Validate the supported webhook authenticity and event scope, then handle it idempotently Correct answer.
  2. Trust every request containing a plausible asset identifier
  3. Treat the request’s source display name as the API secret
  4. Publish the result before checking which operation the event describes

Explanation

A consequential event handler needs the actual supported authenticity and scope checks, along with appropriate retry/idempotence handling. A plausible identifier alone does not establish that the notification is trustworthy.

Question 19Media access, restricted sources and processing safety

A media workflow should fetch only from approved origins. Which design best addresses retrieval of arbitrary unapproved remote content?

  1. Add a descriptive tag and treat that as a network allowlist
  2. Restrict fetch sources through the supported trusted-origin controls and validate the intended workflow Correct answer.
  3. Permit all remote sources because the resulting asset receives a public identifier
  4. Use a wider crop box to prevent remote-origin abuse

Explanation

A fetch workflow needs supported source restrictions and appropriate validation. Asset identifiers, crop geometry and tags do not establish that a remote source is approved or safe.

Question 20Media access, restricted sources and processing safety

A team marks an original asset private and assumes every transformed representation must now have identical access behavior. What should be verified?

  1. Nothing, because private universally means every cached variant is unreachable
  2. Only that the output has the same file extension
  3. The supported original and derived-delivery rules, including strict/signing controls where relevant Correct answer.
  4. Only that the public identifier contains a slash

Explanation

Private originals and transformed delivery can have different supported rules. Verify actual access type, allowed generation and cached representations rather than infer a universal guarantee from one label.

Question 21Image/video transformations, geometry and visual intent

In a supplied Cloudinary crop using a separate supported automatic-gravity qualifier, which listed mode resizes/crops to fill the requested exact dimensions?

  1. c_fit
  2. c_fill Correct answer.
  3. c_scale
  4. c_limit

Explanation

c_fill provides the fill-crop geometry among these alternatives. The separately configured supported gravity determines the retained region; c_fill alone does not imply automatic subject detection. Verify the actual output and source dimensions against visual requirements.

Question 22Image/video transformations, geometry and visual intent

A developer applies the transformation `w_400,h_300,c_crop,g_face` to a portrait photo. What does `g_face` control in this context?

  1. Applies a face-detection AI effect to blur all faces
  2. Sets the crop anchor to the detected face region Correct answer.
  3. Adds an overlay face mask on top of the image
  4. Filters out any image that contains no face

Explanation

g_face (gravity: face) tells Cloudinary to use AI-based face detection to identify the primary face in the image and center the crop around it. This ensures the face is not cut off during cropping. It does not blur, overlay, or filter images.

Question 23Image/video transformations, geometry and visual intent

In a Cloudinary transformation URL, what does chaining transformations with a forward slash separator accomplish?

  1. It creates a folder path where the derived image is cached
  2. It applies each transformation step sequentially, where the output of one step is the input to the next Correct answer.
  3. It splits the image into separate files for each transformation step
  4. It tells the CDN to apply transformations in parallel to reduce latency

Explanation

Cloudinary transformation chains use `/` to separate steps, applying them in order: the output of step N becomes the input for step N+1. This enables complex pipelines such as resize, then overlay, then quality optimization. Each chain step is a distinct transformation component.

Question 24Image/video transformations, geometry and visual intent

Which gravity value should you use to crop an image keeping both detected faces in frame when there are multiple people in the photo?

  1. g_face
  2. g_faces Correct answer.
  3. g_auto
  4. g_center

Explanation

g_faces (plural) uses Cloudinary's face detection to find all detected faces and adjusts the crop to keep the entire group in frame. g_face (singular) only centers on the primary single face. g_auto uses general content-aware detection. g_center uses the geometric center.

Question 25Image/video transformations, geometry and visual intent

A Cloudinary URL includes the transformation segment `e_blur:300`. What does the `:300` value specify?

  1. The pixel radius of the Gaussian blur
  2. The strength/intensity of the blur effect on a 1-2000 scale Correct answer.
  3. The percentage of the image area to blur
  4. The number of blur passes applied

Explanation

The numeric effect qualifier controls the specified blur intensity in the supported Cloudinary syntax. Actual allowed ranges and input behavior require the current parameter reference. This example identifies the role of300 rather than asserting one universal minimum/range for every effect or media type.

Question 26Image/video transformations, geometry and visual intent

In Cloudinary's transformation URL syntax, how do you add a text overlay that reads 'SALE' in white bold Arial at 40px onto an image?

  1. l_text:Arial_40_bold:SALE,co_white Correct answer.
  2. overlay_text:Arial:40:SALE,color_white
  3. e_text:SALE,font_Arial_40
  4. text:SALE,style_Arial_40_bold,color_white

Explanation

Cloudinary text overlays use the syntax l_text:{font}_{size}_{style}:{text},co_{color}. So l_text:Arial_40_bold:SALE applies a bold 40px Arial overlay with co_white setting the text color to white. The l_ prefix denotes a layer (overlay).

Question 27Image/video transformations, geometry and visual intent

A Cloudinary SDK method `cloudinary.url('sample.jpg', {transformation: [{width:300, crop:'fill'}, {effect:'grayscale'}]})` produces a URL with which characteristic?

  1. Both transformations are merged into a single URL step
  2. The URL contains two chained transformation segments separated by a slash Correct answer.
  3. The SDK generates two separate delivery URLs
  4. The grayscale effect is applied before the crop due to SDK optimization

Explanation

When an array of transformation objects is passed to the SDK's url() method, each object becomes a separate chained step in the URL, separated by slashes. This preserves the sequential order: fill-crop first, then grayscale.

Question 28Image/video transformations, geometry and visual intent

Which Cloudinary AI feature automatically identifies the most visually interesting part of an image for cropping, without relying solely on faces?

  1. g_faces
  2. g_auto Correct answer.
  3. e_art
  4. e_background_removal

Explanation

g_auto uses Cloudinary's AI-powered salient region detection to determine which area of the image is most visually important regardless of content type. It works for landscapes, products, and scenes where face detection would not apply.

Question 29Image/video transformations, geometry and visual intent

In Cloudinary, what does the `ar_` transformation parameter control?

  1. The audio bitrate of a video file
  2. The aspect ratio of the output image or video Correct answer.
  3. The archive format when downloading assets
  4. The accuracy level of face recognition

Explanation

ar_ sets the aspect ratio (e.g., ar_16:9 or ar_1.5). It is used in combination with a dimension (w_ or h_) and a crop mode that supports aspect ratio enforcement to resize the asset to the specified ratio.

Question 30Image/video transformations, geometry and visual intent

Which Cloudinary transformation removes the background from a product photo using AI?

  1. e_bgremoval
  2. e_background_removal Correct answer.
  3. e_remove_background
  4. e_cutout

Explanation

e_background_removal is the Cloudinary AI effect that uses machine learning to detect and remove the background from product images, outputting a transparent PNG. This is a paid add-on feature available in Cloudinary's transformation pipeline.

Question 31Image/video transformations, geometry and visual intent

In Cloudinary, what is the difference between `c_thumb` and `c_fill` crop modes?

  1. c_thumb only works on video assets; c_fill works on both images and videos
  2. c_thumb uses gravity-aware cropping optimized for thumbnail faces/objects; c_fill crops to exact dimensions using center gravity by default Correct answer.
  3. c_thumb preserves transparency; c_fill does not
  4. c_thumb downscales only; c_fill can upscale to fill the target dimensions

Explanation

c_thumb is specifically designed for thumbnail generation and uses gravity settings (especially g_face) to crop tightly around a region of interest. c_fill fills the target dimensions with the image, defaulting to center gravity when no gravity is specified. Both crop to exact dimensions.

Question 32Image/video transformations, geometry and visual intent

You need to apply a watermark image overlay to all product images and position it 10px from the bottom-right corner. Which transformation string achieves this?

  1. l_watermark,g_south_east,x_10,y_10 Correct answer.
  2. overlay=watermark&position=bottom-right&margin=10
  3. e_watermark:10,gravity=south_east
  4. mask_watermark,corner=br,offset=10

Explanation

Cloudinary uses l_ for image overlay layer, g_south_east for bottom-right gravity, and x_/y_ for pixel offsets from the gravity anchor. So l_watermark,g_south_east,x_10,y_10 places the watermark 10px from the bottom-right corner.

Question 33Image/video transformations, geometry and visual intent

What is the correct Cloudinary transformation to trim silent/white borders from around an image automatically?

  1. e_trim Correct answer.
  2. c_trim
  3. e_border_remove
  4. c_auto_trim

Explanation

e_trim removes background borders from an image by detecting and cropping uniform color regions at the edges. The effect uses color similarity thresholds and is useful for removing white borders on product images before adding new backgrounds or padding.

Question 34Image/video transformations, geometry and visual intent

Which Cloudinary transformation effect converts an image to grayscale?

  1. e_grayscale Correct answer.
  2. e_black_white
  3. e_desaturate
  4. e_colorize:0

Explanation

e_grayscale converts the image to a grayscale (black and white) rendering by removing all color saturation. It is a standard Cloudinary effect that works on both JPEG and PNG outputs.

Question 35Image/video transformations, geometry and visual intent

Which Cloudinary transformation converts a multi-page PDF into individual image pages that can be accessed by page index?

  1. f_jpg with pg_1,pg_2 chained transformations
  2. resource_type:image with pg_ parameter for page selection Correct answer.
  3. e_pdf_to_images with split:true
  4. upload the PDF as raw and use fl_attachment for each page

Explanation

When a PDF is uploaded with resource_type:image, Cloudinary can access individual pages using the pg_ (page) parameter in the delivery URL. For example, pg_2 delivers the second page as an image. This works for PDFs, PSDs, AI files, and other multi-page formats.

Question 36Image/video transformations, geometry and visual intent

What does the Cloudinary `e_art:{filter}` transformation do?

  1. Applies AI object detection to tag artistic content
  2. Applies a predefined artistic style filter (such as athena, aurora, or peacock) to the image Correct answer.
  3. Converts the image into vector art
  4. Generates NFT-ready metadata for the image

Explanation

e_art:{filter_name} applies one of Cloudinary's built-in artistic style presets to the image, transforming its visual style (e.g., e_art:athena gives a muted vintage look, e_art:peacock gives vivid colors). These are Instagram-filter-like effects.

Question 37Image/video transformations, geometry and visual intent

What does the `bo_` parameter in a Cloudinary transformation add to an image?

  1. Background opacity
  2. A border around the image Correct answer.
  3. Bottom overlay positioning
  4. Black-and-white output mode

Explanation

bo_ (border) adds a pixel border around the image. The syntax is bo_{width}px_solid_{color} (e.g., bo_3px_solid_black). It draws a border within the image's final dimensions. Color can be specified as a hex value or named color.

Question 38Image/video transformations, geometry and visual intent

What is the purpose of the `x_` and `y_` parameters in a Cloudinary transformation that includes an overlay?

  1. They set the absolute pixel coordinates of the overlay from the top-left corner of the base image
  2. They set the pixel offset of the overlay relative to its gravity anchor point Correct answer.
  3. They define the scale factor for the overlay image
  4. They specify the x/y pixel crop coordinates of the base image

Explanation

In Cloudinary overlay transformations, x_ and y_ define the pixel offset from the gravity anchor (g_) point. For example, g_south_east,x_20,y_20 places the overlay 20px inward from the bottom-right corner. The offset direction depends on the gravity setting.

Question 39Image/video transformations, geometry and visual intent

In Cloudinary, what is the effect of combining `c_pad` with `b_auto` on a portrait image being resized to a landscape 16:9 canvas?

  1. The image is cropped to 16:9 using the auto-gravity center
  2. The image is letterboxed with a background color automatically detected from the image edges Correct answer.
  3. The image is stretched to fill the 16:9 canvas
  4. The image background is removed and replaced with a gradient

Explanation

c_pad fits the image within the target dimensions without cropping and adds padding in the remaining space. b_auto fills that padding with a color sampled from the image's edges, creating a natural-looking extension rather than a solid color bar.

Question 40Image/video transformations, geometry and visual intent

What does the `c_lfill` crop mode do in Cloudinary?

  1. Fills the image with a left-aligned crop
  2. Limits the fill crop to the image's original dimensions without upscaling Correct answer.
  3. Applies a low-quality fast fill for thumbnail previews
  4. Fills with landscape orientation enforced

Explanation

c_lfill (limited fill) works like c_fill but only downscales - if the source image is smaller than the target dimensions, it will not be upscaled. This prevents blurry results when small images are requested at large dimensions.

Question 41Image/video transformations, geometry and visual intent

In Cloudinary, what are 'variables' in the context of URL transformations?

  1. Environment variables that configure the Cloudinary SDK
  2. Named user-defined expressions that can be computed and reused within a transformation chain Correct answer.
  3. A/B test variants for different image transformations
  4. Template parameters substituted server-side before URL signing

Explanation

Cloudinary transformation variables (introduced with the $var syntax) allow you to define computed values (e.g., $w:300) and reference them later in the same transformation chain. This enables conditional and reusable transformations within a single URL.

Question 42Image/video transformations, geometry and visual intent

When a Cloudinary transformation URL includes `if_w_gt_500` before a transformation step, what does this accomplish?

  1. It fails the request with a 400 error if the image is wider than 500px
  2. It applies the following transformation step only if the image width is greater than 500px Correct answer.
  3. It sets the output width to a maximum of 500px
  4. It applies a warning flag visible in the Cloudinary console if width exceeds 500px

Explanation

Cloudinary conditional transformations use the if_{expression} parameter. if_w_gt_500 means 'if image width > 500'. The transformation step that follows is applied only when the condition is true, enabling dynamic behavior within a single URL.

Question 43Image/video transformations, geometry and visual intent

What is the Cloudinary `e_sharpen` effect and when would you use it?

  1. It compresses images using a sharper DCT algorithm for better quality/size ratio
  2. It increases edge definition and detail contrast in an image, useful for photos that appear slightly soft after resizing Correct answer.
  3. It converts images to vector-sharp SVG format
  4. It sharpens text overlays to improve readability

Explanation

e_sharpen applies an unsharp mask or similar sharpening algorithm to enhance edge detail and apparent sharpness. This is commonly applied after resizing (which introduces slight softness) to restore perceived crispness. The strength can be controlled with a numeric qualifier.

Question 44Image/video transformations, geometry and visual intent

What does Cloudinary's `e_colorize:{strength}` effect do?

  1. Saturates all colors in the image by the given percentage
  2. Fills the image with a solid color at the given opacity level (0-100)
  3. Applies a color tint of the specified color at the given strength level over the image Correct answer.
  4. Converts the image to a monotone version using the specified color

Explanation

e_colorize:{strength} applies a color tint (specified with the co_ parameter) to the image at the given strength (0-100). For example, e_colorize:50,co_red overlays a 50% strength red tint. Combined with grayscale, it creates a duotone or sepia-style effect.

Question 45Image/video transformations, geometry and visual intent

What does the Cloudinary `e_sepia` transformation effect produce?

  1. A high-contrast black and white rendering
  2. A warm brownish tone that mimics old photograph processing Correct answer.
  3. A cool blue-tinted monochrome effect
  4. An inverted color negative effect

Explanation

e_sepia applies a classic sepia tone (warm brownish tint) to an image, mimicking the look of aged, chemically processed photographs. A strength value (1-100) can be added to control intensity.

Question 46Image/video transformations, geometry and visual intent

What does the `e_pixelate_faces` Cloudinary effect do?

  1. Detects and pixelates only the face regions in an image while leaving the rest unchanged Correct answer.
  2. Applies a pixelation effect to the entire image based on the number of detected faces
  3. Blurs the faces and pixelates the background
  4. Removes faces from the image and fills with background content

Explanation

e_pixelate_faces uses Cloudinary's face detection to automatically locate all faces in the image and applies a pixelation effect only to those regions, leaving the rest of the image intact. This is commonly used for privacy compliance in user-generated content.

Question 47Image/video transformations, geometry and visual intent

Which Cloudinary transformation approach would correctly round the corners of an image by 20px?

  1. r_20 Correct answer.
  2. e_round_corners:20
  3. c_round:20
  4. border_radius:20

Explanation

The r_ (radius) parameter rounds the corners of the image. r_20 applies a 20px corner radius. Use r_max for a fully circular/pill crop. The output should be in a format supporting transparency (PNG or WebP) to see the transparent corners.

Question 48Image/video transformations, geometry and visual intent

How do you create a perfectly circular thumbnail of a person's face at 100x100px in Cloudinary?

  1. w_100,h_100,c_fill,g_face,r_max Correct answer.
  2. w_100,h_100,c_crop,g_face,r_50
  3. w_100,h_100,c_thumb,e_circle
  4. w_100,h_100,e_circle,g_face

Explanation

Combining w_100,h_100 (square dimensions), c_fill (fill the square cropping to the face), g_face (center on the detected face), and r_max (maximum radius = 50px for a 100px image = perfect circle) produces a circular face thumbnail.

Question 49Image/video transformations, geometry and visual intent

Which transformation would produce an image with the top half in color and the bottom half in grayscale?

  1. Split the image into two separate assets and composite them
  2. Use e_grayscale with a region qualifier limiting the effect to the bottom half
  3. Use if_ condition to apply e_grayscale only to pixels below the midpoint
  4. Apply e_grayscale to the full image, then overlay the original top half with l_{public_id} Correct answer.

Explanation

To apply different effects to different regions, overlay the original (or a transformed version) on top. Apply e_grayscale to the whole image, then overlay the original image on the top half (g_north with appropriate h_ or y_ position). Cloudinary does not support regional effect application directly via region qualifiers for e_grayscale.

Question 50Image/video transformations, geometry and visual intent

What does the Cloudinary `e_contrast:{level}` effect do?

  1. Sets the JPEG quality level based on contrast analysis
  2. Adjusts the contrast of the image where positive values increase and negative values decrease contrast Correct answer.
  3. Converts the image to a high-contrast black and white rendering
  4. Applies a contrast-limited adaptive histogram equalization (CLAHE) to the image

Explanation

e_contrast:{level} adjusts image contrast on a scale of -100 to 100. Positive values boost contrast (making darks darker and lights lighter), while negative values reduce contrast. The default is 0 (no change).