DEV Community: Hari Om Patel

5 Ways to Use Universal Google Image Bulk Downloader Pro

Hari Om Patel — Tue, 01 Sep 2026 11:47:07 +0000

Not every developer needs a full-blown image scraping pipeline — but for the ones who do, manually sourcing hundreds or thousands of pictures one by one just isn't realistic. Universal Google Image Bulk Downloader Pro, an open-source Python tool by hariompatel61, was built specifically to close that gap. Here are some of the practical ways it can be put to work.

1. Populating an E-Commerce Catalog

If you're building or seeding an online store, every product listing needs an image — and sourcing hundreds of them manually is one of the most tedious parts of catalog setup. Feed the tool a spreadsheet of product names (say, "clothing_catalog.xlsx" with a search context of "clothing apparel flat lay"), and it fills an output folder with relevant, appropriately sized images while filtering out irrelevant results like model shots if that's not what you need.

2. Building Datasets for AI Training

Training image classifiers or generative models requires large, labeled sets of visual examples. Rather than hand-collecting images, this tool can generate a bulk dataset from a simple list of category names — for example, a list of food dishes, each becoming its own labeled folder of sample images — dramatically speeding up the data-collection phase of a machine learning project.

3. Filling Out a Restaurant or Menu App

The project's own sample output — a canteen menu spreadsheet ("Study_Break_College_Canteen_Menu.xlsx") turned into images of samosas, dosas, idlis, and poha — is a direct example of this use case. Any food-ordering site, digital menu board, or delivery app that needs a photo for every dish can automate that step instead of sourcing each image by hand.

4. Content Management Systems and Blogs

Sites that publish a high volume of structured content — think product review blogs, directory listings, or niche content sites — often need a matching image for every entry. The config-driven job queue means you could run separate scraping jobs for different content categories in one pass, each with tailored search terms.

5. General Research and Personal Projects

Because it's MIT-licensed and free to modify, the tool is also a solid starting point for anyone learning Selenium automation, working on a personal side project, or doing small-scale visual research where manually searching and saving images would eat up hours.

A Word on Responsible Use

Worth repeating: the project's own documentation is explicit that this is meant for personal, educational, and research purposes, and that downloading an image doesn't transfer its copyright to you. If you're using output commercially — for a real storefront or a public app — you're responsible for confirming you have the rights to use whatever images the tool pulls down. The built-in rate limiting also exists for a reason: it's there to avoid putting unreasonable load on the search engines it queries, and the README explicitly asks users not to strip it out.

Explore the code and configuration options here: github.com/hariompatel61/universal-image-downloader

Inside the Architecture: How Universal Google Image Bulk Downloader Pro Avoids Getting Blocked

Hari Om Patel — Tue, 01 Sep 2026 11:43:38 +0000

Most home-grown image scrapers fall apart the same way: they get CAPTCHA-walled after a few dozen requests, or they return a pile of irrelevant junk mixed in with the images you actually wanted. Universal Google Image Bulk Downloader Pro, an open-source project by hariompatel61, tackles both problems with a handful of deliberate architectural choices worth breaking down.

1. Undetected ChromeDriver + Persistent Sessions

Rather than relying on a headless request library, the tool drives a real, undetected instance of Chrome via undetected-chromedriver. This matters because standard Selenium/ChromeDriver setups leave detectable fingerprints that anti-bot systems flag quickly.

The bigger trick, though, is session persistence. The first time you run the script, if Google throws a CAPTCHA at you, you get a short window to solve it manually. From that point on, the session cookies are stored in a local chrome_profile/ folder, so every subsequent run reuses that trusted session instead of starting from a blank, suspicious slate.

2. A Two-Tier Search Strategy

Instead of firing a single generic query at Google Images, the tool runs a layered search:

Tier 1 (Premium First): It biases results toward known stock photography domains — Freepik, Unsplash, Pexels, Pixabay — which tend to produce cleaner, higher-quality, and more consistently licensed-adjacent imagery.
Tier 2 (Intelligent Fallback): If the premium tier doesn't return enough usable results, it drops back to general Google Images search, but appends negative filters (like -recipe -video) defined per job in config.json. This is what keeps a "food dish" search from returning cooking-tutorial thumbnails instead of clean product shots.

3. Config-Driven, Multi-Job Processing

Rather than hardcoding search behavior, everything lives in config.json. Each entry in the jobs array is essentially an independent scraping task: its own source spreadsheet, its own column mappings, its own search_context string, its own fallback filters, and its own output folder. That means a single script run can process an entirely different search strategy for a clothing catalog than it does for a food menu — no code changes required, just config edits.

4. Smart Header Detection

Real-world spreadsheets are messy. The tool is built to tolerate that — parsing single-column lists, two-column files with names and categories, or files with custom headers — rather than requiring a rigid, pre-formatted template.

5. Resume-and-Skip Logic

Long scraping jobs are fragile; a dropped connection partway through a 1,000-item list used to mean starting over. This tool checks the output folder before each download and skips anything that already exists, so interrupted runs can simply be restarted without wasted bandwidth or duplicate work.

6. Built-In Rate Limiting

Perhaps the most understated but important design decision: the script bakes in randomized delays — roughly 1.5 to 3.5 seconds between actions, with longer page waits around 3.5 seconds — keeping the average request rate around 10–15 per minute. This isn't just about avoiding bans; it's a basic courtesy to the search infrastructure being used, and the README explicitly warns against stripping these delays out.

The Net Result

None of these ideas — undetected browser automation, tiered search, config-driven job queues, resume logic, rate limiting — are individually novel. What makes this project useful is that they're combined into a single, MIT-licensed, ready-to-run tool instead of being something you'd have to stitch together yourself.

Source code and full configuration reference: github.com/hariompatel61/universal-image-downloader

# How to Set Up Universal Google Image Bulk Downloader Pro (Step-by-Step)

Hari Om Patel — Tue, 01 Sep 2026 11:38:32 +0000

Bulk-downloading clean, high-resolution images from an Excel list sounds complicated — but the open-source Python tool Universal Google Image Bulk Downloader Pro by hariompatel61 makes it a five-minute setup. Here's exactly how to get it running.

Prerequisites

Before you start, make sure you have:

Python 3.8+ installed
Google Chrome installed on your machine (the tool automates a real Chrome browser under the hood)

Step 1: Clone the Repository

Open a terminal and run:

git clone https://github.com/hariompatel61/universal-image-downloader.git
cd universal-image-downloader

Step 2: Install Dependencies

The project ships with a requirements.txt covering everything it needs:

undetected-chromedriver>=3.5.5
selenium>=4.21.0
pandas>=2.0.0
openpyxl>=3.1.2
Pillow>=10.0.0
requests>=2.31.0

Install them all in one line:

pip install -r requirements.txt

Step 3: Prepare Your Data File

The tool expects an Excel (or CSV) file listing the items you want images for. A simple one-column list of item names works, but you can also include a category column for more targeted search results — the tool has smart header detection built in, so messy sheets aren't a dealbreaker.

Step 4: Configure `config.json`

On first run, the script generates a config.json file. This is where the real customization happens — you can set:

premium_sites: which stock photo sites to prioritize (Freepik, Unsplash, Pexels, Pixabay by default)
min_width / min_height: minimum acceptable image resolution
jobs: an array of tasks, each pointing at a different data file, with its own search_context (e.g., "Indian food dish") and fallback_filters (e.g., -recipe -video -youtube) to keep results clean

This job-queue structure means you can process several spreadsheets — say, a food menu and a clothing catalog — in a single run, each with different search logic.

Step 5: Run It

Fire up the script (or use the included RUN_DOWNLOAD.bat on Windows for a one-click start). On the very first run, you'll get about 10 seconds to manually solve a CAPTCHA if one appears. After that, your session cookies are saved in a local chrome_profile/ folder, so you won't be prompted again on future runs.

Handling Common Snags

The project's README includes a small but useful troubleshooting section:

SessionNotCreatedException: usually a Chrome/driver version mismatch. Open the script and update version_main=XXX inside init_driver() to match your installed Chrome version.
Item skipped unexpectedly: the script won't re-download files that already exist in your output folder. Delete the old file if you want a fresh copy.

That's It

Once configured, the script runs hands-free — parsing your spreadsheet, searching, filtering, and saving images into the output folder you specified, while respecting built-in rate limits (roughly 10–15 requests per minute) so you don't get your IP banned for hammering search engines.

Full docs and source: github.com/hariompatel61/universal-image-downloader

Bulk Image Downloader from Excel with Product Name (Anti-CAPTCHA + Auto-ZIP)

Hari Om Patel — Tue, 01 Sep 2026 11:18:46 +0000

If you've ever tried building an E-commerce catalog, digital canteen menu, or an AI training dataset, you probably know the pain: you have a list of hundreds of product names in an Excel sheet, but no images.

When you search for a solution like "bulk image downloader through excel with product name", almost every existing tool fails because:

They expect direct image URLs, not simple product names.
Google blocks automated requests with CAPTCHAs after just 5–10 searches.
Images are messy (recipe screenshots, watermarked logos, or low-res thumbnails).

To solve this once and for all, I built and open-sourced Universal Google Image Bulk Downloader Pro — a Python automation tool that takes product names directly from an Excel/CSV sheet, fetches high-resolution images, and automatically packages everything into a ZIP file.

⭐ GitHub Repo: https://github.com/hariompatel61/universal-image-downloader

⚡ What Makes This Different?

Feature	Regular Image Scrapers	Universal Image Downloader Pro
Input Format	Direct image URLs only	Plain Product Names in Excel / CSV
Anti-CAPTCHA	❌ Gets blocked fast	✅ `undetected-chromedriver` session profile
Search Quality	❌ Random messy photos	✅ Stock sites first (Freepik, Unsplash, Pexels)
Packaging	❌ Manual	✅ Automatic ZIP Archive (`.zip`)
Resume Support	❌ Redownloads everything	✅ Smart Skip logic (>5KB)

🛠️ How It Works (Under the Hood)

1. Two-Tier Smart Search Strategy

Tier 1 (Stock Photography First): It first searches Google specifically targeting curated high-res stock sources (Freepik, Unsplash, Pexels, Pixabay).
Tier 2 (Filtered Fallback): If no stock image matches, it falls back to Google Images while automatically stripping noisy terms like -recipe, -video, -youtube.

2. Bypass CAPTCHA with Persistent Sessions

Using undetected-chromedriver and a dedicated user profile folder (chrome_profile/), you only solve a CAPTCHA once (if prompted). Subsequent runs retain session cookies, preventing Google from throwing bot challenges.

3. Automatic ZIP & Audit Trail

Once all rows are processed:

All valid images are bundled into <output_folder>.zip (e.g., product_images.zip).
A clean .csv audit report is generated listing item status, file names, and download sources.

🚀 Quick Start Guide

Step 1: Clone & Install Dependencies


bash
git clone https://github.com/hariompatel61/universal-image-downloader.git
cd universal-image-downloader
pip install -r requirements.txt

🚀 I Built 14 Free Image Tools That Run 100% in Your Browser (No Uploads)

Hari Om Patel — Sat, 07 Mar 2026 04:48:47 +0000

Most online image tools require you to upload your files to a server.
This can be slow, and it also raises privacy concerns since your files leave your device.

I wanted to build something different.

So I created a small project: a collection of free image tools that run entirely in the browser.

No uploads.
No signup.
No server processing.

Everything happens locally on your device using browser APIs.

🌐 The Project

🔗 https://imageconverttools.site

The idea behind the project was simple:

Build a fast, privacy-focused toolkit for common image tasks that people use every day.

Instead of sending images to a backend server, the tools process files directly in the browser.

This approach provides several advantages:

✅ Faster processing
✅ No server costs
✅ Better privacy
✅ Instant results

🧰 Tools Included

Currently the platform includes 14 different tools for working with images.

Image Converters

• PNG → JPG
• JPG → PNG
• WebP Converter
• SVG → PNG

Image Editing Tools

• Image Compressor
• Image Resizer
• Image Cropper
• Rotate & Flip
• Image Filters

Utility Tools

• Image → PDF converter
• Watermark tool
• Base64 encoder / decoder
• Meme generator

Special Tool

• Government exam photo resizer (for SSC, UPSC, and other forms)

⚙️ How It Works

The tools rely heavily on client-side browser processing.

Technologies used include:

HTML5 Canvas API

JavaScript image manipulation

FileReader API

Client-side image compression

Instead of sending images to a server, the browser handles everything locally.

Typical workflow

1️⃣ User selects an image
2️⃣ The browser reads the file using FileReader
3️⃣ Image processing happens through the Canvas API
4️⃣ The processed image is instantly downloaded

This eliminates the need for server-side image processing, making the tools faster and more private.

🚀 Why I Built This

While working on various projects, I kept running into the same small problems:

Compressing images

Converting file formats

Resizing photos for online forms

Most tools I found online were:

❌ slow
❌ overloaded with ads
❌ required uploading files

So I decided to build a simple and lightweight alternative focused on speed and privacy.

📈 What’s Next

I’m planning to expand the platform with more tools, such as:

• Background remover
• AI image enhancer
• Passport photo maker
• Batch image converter
• Screenshot editing tools

The long-term goal is to build a complete online image toolkit.

💬 Feedback Welcome

I’d love to hear feedback from the developer community.

Some questions I'm exploring:

What tools should be added next?

Are there performance improvements I should explore?

Any interesting browser APIs worth experimenting with?

You can try the project here:

👉 https://imageconverttools.site

🧠 Final Thoughts

Building small utility tools is a great way to:

• Learn browser APIs
• Solve real-world problems
• Experiment with micro-products

Sometimes the simplest tools turn out to be the most useful.