imgsea – image sharing made beautiful.

Hacker News

Hey guys! My friend, Abhishek and I (Arjit) have been working on our new image sharing service "imgsea" we have worked on imgsea for about 3 months now and have coded the site from ground up, we use the popular CSS framework Bootstrap for our website's UI. Currently we have the following features enabled : 1. Ability to upload images (YAY!) 2. Ability to create a custom album out of your uploaded images 3. Ability for users to comment on your images 4. Timeline like image display layout (TimeFlow) 5. Share picture on social networks (Facebook etc) 6. Passwords hashed with Crypt 7. Multiple image upload at once What's coming ? 1. Social networking functions like Private messaging, chat, friend list and a wall like feature. 2. Ability to download all your pictures in 1 go (.zip) 3. SSL/HTTPS secured login (top priority at the moment) 4. Multiple image serving VPSes to serve images from multiple locations to ease off the load on the main host and serve images faster as well. 5. Drag & Drop upload So what's the current limits? Currently the only limits are each image is limited to a max of 20 MB. What we would like ? Report any and every bug you find :) at https://bitbucket.org/arjitc/imgsea-v2/issues?status=new&status=open We're open to suggestions/feedback/criticism and feature requests as well. Finally the link to imgsea, http://imgsea.com Thanks :D

Visit product View on Hacker NewsFeb 11, 2014

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

91%91% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, code · Missing: mac, agents, macos

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: month, users · Missing: mobile apps, ios, personal

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: host, users · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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