scraping images from a database: 70,000 references

My goal is to recover as many images as possible from a file comprising between 70 and 80,000 product references. The supplied file (xlsx) includes the brand, the GTIN code, the manufacturer reference (MPN) and the description.

The images should be sought in priority on the sites of the manufacturers. If there are no images on the manufacturer's site, then another image can be found.

The images found must be renamed with the GTIN code. The first like GTIN-1, the second like GTIN-2 ... (for example, if the GTIN is 5449000000996, the first image found will be renamed: 5449000000996-1, the second 5449000000996-2 ...)

Images with a watermark should be avoided as much as possible. I am only looking for solutions with algorithm.

Keep in mind: There are a lot of images to look for: 80,000 references with an average of 5 images per product. So you need someone who develops a script. For the quality, this script must first browse the sites of the manufacturers. The names of the manufacturers are entered in the file.

The operation must be completely finished by Friday, October 29. Imperative deadline.

Evner: Web Skrabning, Datasøgning, Python, Databehandling, Dataindførsel

Se mere: zen cart save images database, dotnetnuke images database, save drag drop images database using php, php images database, extract images database php, copy paste images database fields access, read images database jsp hibernate, free images database next prev, extract images database using php, extracting blob images database, slideshow dynamic images database, load images database flash, joomla images database, scrolling flash images database, casino images database, upload images database php, images database filesystem, possible extract images database

Om arbejdsgiveren:
( 2 bedømmelser ) LESQUIN, France

Projekt ID: #31891334

Tildelt til:

(17 bedømmelser)

44 freelancere byder i gennemsnit €464 timen for dette job

(88 bedømmelser)
(574 bedømmelser)
(400 bedømmelser)

Hello Sir, I am an expert in web research,I saw the details and I understood well how to execute this task within the mentioned timeline . Please contact me to discuss more ,looking forward to work with you. Thanks.

€550 EUR in 8 dage
(968 bedømmelser)
(117 bedømmelser)
(130 bedømmelser)

Hello, I hope you are doing great. I have good experience with doing similar jobs. You can check my portfolio here: https://www.freelancer.com/u/AwaisChaudhry?w=f I can do this job because have great experience with Py Flere

€550 EUR in 29 dage
(9 bedømmelser)

hi there, I will make a script/BOT to download these images. (as I only do WEB SCRAPING and not MANUAL DATA ENTRY work) The script will take product reference numbers from the file and search on the respective manufact Flere

€250 EUR in 2 dage
(209 bedømmelser)
(174 bedømmelser)
(93 bedømmelser)
(90 bedømmelser)
(49 bedømmelser)

I am a Data Scientist with Machine Learning Expertise. Please take a look at my profile and reviews for references.

€480 EUR in 7 dage
(10 bedømmelser)
(17 bedømmelser)

ok sure i can scarp images 70 to 80,000 product references as you want before Friday, October 29 deadline pls PM me can we discuss more ..? wait for reply thanks.

€250 EUR in 7 dage
(38 bedømmelser)

We will do your scrapping work I am writing this proposal in order to work for you in Software and Web Development. We are highly trained professional developers seeking to freelance and earn online. Having a flair in Flere

€480 EUR in 7 dage
(16 bedømmelser)
(13 bedømmelser)
(7 bedømmelser)

Hello. I have read your job description and It makes me interest. I am a 7+ years experienced Software developer who is good at DataScraping. I will maintain good communication with you and I can work in your time zone Flere

€500 EUR in 5 dage
(2 bedømmelser)

Hi! I'm 5 years experienced Data Scientist with theoretical and practical experience in Data Science, Machine Learning & Deep Learning ready to do your work in an efficient way with strong analytical and logical reason Flere

€500 EUR in 4 dage
(12 bedømmelser)