Adobe Stock Image Scraper | Fast & Reliable
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from $0.70 / 1,000 results
Adobe Stock Image Scraper | Fast & Reliable
Extract Adobe Stock assets at scale with rich metadata, creator data, thumbnails, dimensions, licensing flags, category signals, and advanced filters. Built for enterprise-grade visual intelligence, creative research, asset discovery, and automated data pipelines.
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from $0.70 / 1,000 results
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Fatih Tahta
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Adobe Stock Image Scraper
Slug: fatihtahta/adobe-stock-image-scraper
Overview
Adobe Stock Image Scraper collects structured Adobe Stock asset records, including titles, asset identifiers, asset URLs, thumbnails, dimensions, creator information, category metadata, licensing flags, and collection context. Adobe Stock is a large public marketplace for creative assets, making its searchable asset data useful for market research, catalog analysis, creative operations, and monitoring workflows. The actor turns repeatable Adobe Stock searches and filters into normalized JSON records that can be used in analytics tools, data pipelines, dashboards, and enrichment workflows. It is designed for dependable recurring data acquisition with consistent output fields and clear limits, without requiring manual copying or one-off browser work. Results reflect the publicly available data at run time and can be scheduled, exported, or integrated into downstream systems.
Why Use This Actor
- Market research / analytics: collect structured extraction data for asset supply analysis, category comparison, creator coverage, visual trend monitoring, and operational reporting.
- Product & content teams: build repeatable collection workflows for creative asset discovery, campaign planning, content audits, and dataset normalization.
- Developers / data engineering pipelines: feed Adobe Stock records into downstream systems, warehouses, search indexes, and enrichment pipelines using predictable JSON output.
- Lead generation / enrichment: identify creators, categories, asset URLs, and public artist pages that can enrich research or prospecting datasets.
- Monitoring / competitive tracking: schedule recurring runs to observe changes in asset availability, free collection coverage, AI-generated content, media types, and category movement.
Common Use Cases
- Market intelligence: monitor asset supply, category distribution, free availability, creator activity, and visual format coverage across selected searches.
- Creative asset discovery: collect searchable Adobe Stock records for review queues, campaign planning, mood boards, and content selection workflows.
- Competitive monitoring: track visible changes in public creative asset collections, category movement, or creator coverage over time.
- Catalog and directory building: populate owned databases with structured public asset records, thumbnails, creator metadata, and category fields.
- Data enrichment: add current public Adobe Stock attributes to existing BI, CRM, creative operations, or analytics datasets.
- Recurring reporting: schedule periodic collection runs for dashboards, alerts, trend analysis, and historical comparison.
Quick Start
- Choose one or more
queries, or leavequeriesempty for broad discovery. - Add optional filters such as
asset_type,orientation,usage_rights,generative_ai,people,background,icons,vivid_color, orfree_to_usewhen you need a narrower dataset. - Set a small
limit, such as25or50, for the first validation run. - Run the actor in Apify Console.
- Inspect the first dataset records to confirm that the output fields match your workflow.
- Increase
limit, add more search terms, or schedule the actor after the output is verified.
Input Parameters
The actor accepts optional Adobe Stock search terms, asset filters, and a per-target result limit.
| Parameter | Type | Description | Default |
|---|---|---|---|
asset_type | string | Limits keyword searches to one asset type. Allowed values: images, videos, templates, 3d. | – |
queries | array of strings | Optional search terms. Enter one word or phrase per item. Each search term is collected separately when provided. Leave empty for a broader run without a keyword. | – |
undiscovered_content | boolean | Focuses keyword searches on Adobe Stock content marked as not previously downloaded. Availability can vary over time. | false |
background | array of strings | Narrows keyword searches by background or subject format. Allowed values: transparent, isolated_assets. | – |
generative_ai | string | Chooses whether keyword searches focus on generative AI content or exclude it. Allowed values: ai_only, ai_excluded. | – |
icons | array of strings | Narrows keyword searches to icon-specific formats. Allowed values: individual_icon, icon_sheet. | – |
orientation | array of strings | Filters assets by visual orientation. Allowed values: horizontal, vertical, square, panoramic. | – |
people | string | Chooses whether searches include assets with people or focus on assets without people. Allowed values: include_people, exclude_people. | – |
usage_rights | string | Limits keyword searches by usage-rights category. Allowed values: commercial_usage, editorial_usage. | – |
vivid_color | string | Steers searches by color intensity. Allowed values: very_low, low, high, very_high. | – |
free_to_use | boolean | Restricts keyword searches to Adobe Stock assets from the free collection. | false |
limit | integer | Maximum number of records to save for each search term or target. Minimum: 1. | – |
Choosing Inputs
Use queries when you already know the topic, keyword, theme, or asset segment you want to collect. Leave optional filters empty when the goal is broad discovery, then add filters gradually when you need a more targeted dataset. Narrow filters such as asset_type, orientation, usage_rights, generative_ai, people, background, icons, vivid_color, and free_to_use can improve relevance, while broader inputs improve discovery and coverage. Start with a small limit to validate the output shape and increase it after confirming that the records match your downstream requirements.
Example Inputs
Search-driven image collection
{"queries": ["nature", "forest canopy"],"asset_type": "images","orientation": ["horizontal"],"people": "exclude_people","usage_rights": "commercial_usage","limit": 50}
Free icon discovery
{"queries": ["finance dashboard icons"],"asset_type": "images","icons": ["individual_icon"],"free_to_use": true,"vivid_color": "high","limit": 40}
Broad filtered discovery
{"asset_type": "templates","generative_ai": "ai_excluded","background": ["isolated_assets"],"undiscovered_content": true,"limit": 25}
Output
9.1 Output destination
The actor writes results to an Apify dataset as JSON records. The dataset is designed for direct consumption by analytics tools, ETL pipelines, and downstream APIs with minimal post-processing.
When multiple entity types or record shapes exist, the README documents each shape separately based on the provided Example Output. The provided output contains one record shape: an Adobe Stock asset record.
9.2 Record envelope and stable identifiers
Each record represents one Adobe Stock asset and includes identifiers, public asset URLs, media metadata, creator details, category information, availability flags, and source context.
Recommended idempotency key: id. If a downstream system requires a URL-based key, url is also a stable public asset reference, and fingerprint can be retained as a secondary run-level record identifier.
Use the recommended key for deduplication and upserts when syncing repeated runs into warehouses, CRMs, search indexes, or asset catalogs. Stable identifiers make records easier to merge, deduplicate, and sync across repeated runs. The sourceUrl field records the public collection context used for the record, while fingerprint provides an additional deterministic identifier for the saved record.
9.3 Examples
Example: Adobe Stock asset
{"id": "305060700","id32": "HValp62AU5V1ZTWb2kegfnefp7r5kgDs","url": "https://stock.adobe.com/tr/images/looking-up-at-the-green-tops-of-trees/305060700","title": "Looking up at the green tops of trees.","assetType": "Image","mediaTypeLabel": "Photo","contentType": "image/jpeg","format": "jpeg","thumbnailUrl": "https://t4.ftcdn.net/jpg/03/05/06/07/360_F_305060700_HValp62AU5V1ZTWb2kegfnefp7r5kgDs.jpg","thumbnailUrlWebp": "https://t4.ftcdn.net/jpg/03/05/06/07/360_F_305060700_HValp62AU5V1ZTWb2kegfnefp7r5kgDs.webp","largeThumbnailUrl": "https://as2.ftcdn.net/v2/jpg/03/05/06/07/500_F_305060700_HValp62AU5V1ZTWb2kegfnefp7r5kgDs.jpg","extraLargeThumbnailUrl": "https://as2.ftcdn.net/v2/jpg/03/05/06/07/1000_F_305060700_HValp62AU5V1ZTWb2kegfnefp7r5kgDs.jpg","width": 5760,"height": 3840,"author": "proslgn","creatorId": 205763247,"artistPageUrl": "https://stock.adobe.com/tr/contributor/205763247/proslgn?load_type=author","categoryId": 782,"categoryName": "Plants and Flowers","isFree": false,"isPremium": false,"isFireflyGenerated": false,"isVector": false,"isVideo": false,"isImage": true,"isPurchasable": true,"defaultLicenseId": 1,"sourceUrl": "https://stock.adobe.com/tr/Ajax/Search?filters%5Bcontent_type%3A3d%5D=1&filters%5Bcontent_type%3Aaudio%5D=0&filters%5Bcontent_type%3Aillustration%5D=1&filters%5Bcontent_type%3Aimage%5D=1&filters%5Bcontent_type%3Aphoto%5D=1&filters%5Bcontent_type%3Atemplate%5D=1&filters%5Bcontent_type%3Avideo%5D=1&filters%5Bcontent_type%3Azip_vector%5D=1&filters%5Bglobally_safe_collection%5D=1&filters%5Binclude_stock_enterprise%5D=0&get_facets=0&k=nature&limit=100&order=relevance&search_page=1&search_type=asset-type-change","fingerprint": "4a75cf22d1b4473a4134","seed_id": "8e7f35c5a556","seed_type": "query","seed_value": "nature","page_index": 1,"extraction_strategy": "api_json"}
Field Reference
Adobe Stock asset record
- id (string, required): Adobe Stock asset identifier. Recommended idempotency key.
- id32 (string, optional): Secondary asset identifier used by Adobe Stock media URLs.
- url (string, required): Public Adobe Stock asset page URL.
- title (string, optional): Asset title.
- assetType (string, optional): High-level asset type, such as image or video.
- mediaTypeLabel (string, optional): Human-readable media label, such as photo.
- contentType / format (string, optional): Media content type and file format.
- thumbnailUrl (string, optional): Standard thumbnail image URL.
- thumbnailUrlWebp (string, optional): WebP thumbnail image URL.
- largeThumbnailUrl (string, optional): Larger preview thumbnail URL.
- extraLargeThumbnailUrl (string, optional): Extra-large preview thumbnail URL.
- width / height (integer, optional): Asset dimensions in pixels.
- author (string, optional): Public creator or contributor name.
- creatorId (integer, optional): Adobe Stock creator identifier.
- artistPageUrl (string, optional): Public contributor page URL.
- categoryId (integer, optional): Adobe Stock category identifier.
- categoryName (string, optional): Adobe Stock category name.
- isFree (boolean, optional): Whether the asset is marked as part of the free collection.
- isPremium (boolean, optional): Whether the asset is marked as premium.
- isFireflyGenerated (boolean, optional): Whether the asset is marked as Firefly-generated.
- isVector (boolean, optional): Whether the asset is marked as vector content.
- isVideo (boolean, optional): Whether the asset is marked as video content.
- isImage (boolean, optional): Whether the asset is marked as image content.
- isPurchasable (boolean, optional): Whether the asset is marked as purchasable.
- defaultLicenseId (integer, optional): Default license category identifier when provided.
- sourceUrl (string, optional): Public collection context associated with the saved record.
- fingerprint (string, optional): Deterministic record fingerprint for deduplication support.
- seed_id (string, optional): Identifier for the input target that produced the record.
- seed_type (string, optional): Input target type, such as
query. - seed_value (string, optional): Input value that produced the record.
- page_index (integer, optional): Result page number associated with the record.
- extraction_strategy (string, optional): Record source label included for traceability.
Data Quality, Guarantees, And Handling
- Structured records: results are normalized into predictable JSON objects for downstream use.
- Best-effort extraction: fields may vary by region, session, availability, or source-side experiments.
- Optional fields: null-check optional fields in downstream code, especially creator, category, license, and thumbnail metadata.
- Deduplication: use
idas the strongest stable key;urlandfingerprintcan be retained as secondary identifiers. - Freshness: results reflect the publicly available data at run time.
- Repeated runs: use the recommended idempotency key when syncing data into warehouses, CRMs, search indexes, or asset catalogs.
Tips For Best Results
- Start with a small
limitto validate the output shape before scaling up. - Use one theme, asset segment, or search intent per run when you need cleaner segmentation.
- Leave optional filters empty when the goal is broad discovery.
- Add filters gradually to understand how each field changes coverage.
- Use
asset_typeandorientationwhen your workflow depends on a specific media format or layout. - Schedule recurring runs for monitoring workflows instead of relying on manual one-off collection.
- Store
id,url, andfingerprintwhen deduplicating records over time.
How to Run on Apify
- Open the Actor in Apify Console.
- Configure the available input fields for the target scope.
- Set the maximum number of outputs to collect with
limit. - Click Start and wait for the run to finish.
- Open the dataset and review the first records.
- Download results in JSON, CSV, Excel, or another supported format.
Scheduling & Automation
Scheduling
Automated Data Collection
Schedule runs to keep Adobe Stock asset datasets fresh for reporting, monitoring, and enrichment workflows. Recurring runs are especially useful when tracking category movement, free collection availability, creator coverage, or AI-generated asset trends.
- Navigate to Schedules in Apify Console
- Create a new schedule, such as daily, weekly, or a custom cron expression
- Configure input parameters
- Enable notifications for run completion
- Add webhooks for automated processing
Integration Options
- BI dashboards: monitor asset volume, category movement, media mix, free collection coverage, and creator trends over time.
- Data warehouses: store historical Adobe Stock asset records for analysis, reporting, and audit-friendly comparisons.
- ETL pipelines: normalize dataset records into organization-specific schemas for search, analytics, or creative operations platforms.
- Webhooks: trigger validation, ingestion, notification, or downstream processing after each completed run.
- Google Sheets or Airtable: review smaller curated asset collections with content, marketing, or research teams.
- Slack, Discord, or email alerts: notify teams when scheduled monitoring runs complete or when downstream checks detect notable changes.
Export Formats And Downstream Use
Apify datasets can be exported or consumed by downstream systems for operational reporting, review, and automated ingestion.
- JSON: for APIs, applications, and data pipelines.
- CSV or Excel: for spreadsheet workflows and manual review.
- API access: for automated ingestion into owned systems.
- BI and warehouses: for reporting, dashboards, and historical analysis.
Performance
Estimated run times:
- Small runs (< 1,000 outputs): ~3-5 minutes
- Medium runs (1,000-5,000 outputs): ~5-15 minutes
- Large runs (5,000+ outputs): ~15-30 minutes
Execution time varies based on filters, result volume, and how much information is returned per record. Highly filtered runs can finish faster, while broad discovery or detail-rich records may take longer.
Limitations
- Availability depends on what
https://stock.adobe.compublicly exposes at run time. - Some optional fields may be missing on sparse records or asset types with limited metadata.
- Very broad searches may take longer or require higher limits to collect enough useful records.
- Target-side changes can affect field availability, naming, or visible result composition.
- Regional, account, language, or availability differences may change visible results.
- The actor does not guarantee completeness for every possible Adobe Stock result matching a broad topic.
Troubleshooting
- No results returned: check search terms and filters, and verify that Adobe Stock has matching public records for the selected scope.
- Fewer results than expected: broaden filters, raise
limit, or confirm that the target contains enough matching records. - Some fields are empty: optional fields depend on what each record publicly provides.
- Run takes longer than expected: reduce scope, lower
limitfor validation, or split broad collection into smaller segments. - Output changed: compare the current output with the field reference and report a small sample if support is needed.
FAQ
What data does this actor collect?
It collects public Adobe Stock asset records, including asset identifiers, titles, URLs, thumbnails, dimensions, creator metadata, category fields, availability flags, and source context.
Can I filter by location, category, date, price, or other criteria?
The current input schema supports search terms, asset type, background, generative AI status, icon format, orientation, people, usage rights, vivid color, free collection status, undiscovered content, and result limit. It does not include location, date, price, or category input fields.
Why did I receive fewer results than my limit?
The limit is a maximum, not a guarantee. A run can return fewer records when Adobe Stock has fewer matching public results for the selected query and filters.
Can I schedule recurring runs?
Yes. Use Apify schedules to run the actor daily, weekly, or on a custom cron schedule with saved input parameters.
How do I avoid duplicates across runs?
Use id as the primary idempotency key. Retain url and fingerprint as secondary identifiers when your downstream system benefits from additional matching fields.
Can I export the data to CSV, Excel, or JSON?
Yes. Apify datasets support JSON, CSV, Excel, and other export formats from the dataset view.
Does this actor collect private data?
No. The actor is intended to collect publicly available Adobe Stock asset information visible from https://stock.adobe.com.
Does the actor download the licensed asset file?
The output may include public preview image URLs when available. It does not download licensed asset files, grant usage rights, or replace Adobe Stock licensing requirements.
What should I include when reporting an issue?
Include the input used, the run ID, expected versus actual behavior, and a small output sample if it helps illustrate the issue. Redact anything sensitive before sharing.
Compliance & Ethics
Responsible Data Collection
This actor collects publicly available Adobe Stock creative asset information from https://stock.adobe.com for legitimate business purposes, including:
- Creative industry research and market analysis
- Content operations and asset discovery workflows
- Market intelligence and recurring public data monitoring
This section is informational and not legal advice. Users are responsible for ensuring that their use of collected data complies with applicable laws, regulations, and platform terms.
Best Practices
- Use collected data in accordance with applicable laws, regulations, and the target site's terms
- Respect individual privacy and personal information
- Use data responsibly and avoid disruptive or excessive collection
- Do not use this actor for spamming, harassment, or other harmful purposes
- Follow relevant data protection requirements where applicable, such as GDPR and CCPA
Support
For help, use the actor page or Issues section. Include the input used, with sensitive values redacted if needed, the run ID, the expected versus actual behavior, and a small output sample when it helps clarify the problem.