![\"hi\"](\"https://i.ibb.co/tDbJmgh/1-J1qp-G6-TUYsq43wh-Aqezjyg.png\")
When we talk about Object Detection, we are here referring to identifying bounding boxes for different objects of our interest from the image. Bounding boxes are generally defined by the position of the top left corner (2 coordinates) and a width and height (in the number of pixels).
\nwhereas Image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.
\nPlease feel free to add more details on this.
", "messages": [ { "id": "1546332", "postDate": "10/16/2021 03:16:25", "content": "When we talk about Object Detection, we are here referring to identifying bounding boxes for different objects of our interest from the image. Bounding boxes are generally defined by the position of the top left corner (2 coordinates) and a width and height (in the number of pixels).
\nwhereas Image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.
\nPlease feel free to add more details on this.
", "rawMarkdown": "When we talk about Object Detection, we are here referring to identifying bounding boxes for different objects of our interest from the image. Bounding boxes are generally defined by the position of the top left corner (2 coordinates) and a width and height (in the number of pixels).\n \nwhereas Image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.\n\nPlease feel free to add more details on this.", "votes": null }, { "id": "1547730", "postDate": "10/17/2021 14:27:35", "content": "Below external link explains the concept beautifully, thanks @revathiprakash for initiating this topic
\n", "rawMarkdown": "Below external link explains the concept beautifully, thanks @revathiprakash for initiating this topic\n\nhttps://www.geeksforgeeks.org/object-detection-vs-object-recognition-vs-image-segmentation/#:~:text=Image%20segmentation%20is%20a%20further,object%20present%20in%20the%20image.", "votes": null }, { "id": "1548065", "postDate": "10/17/2021 23:33:43", "content": "COPYING FROM MY RESPONSE ON A SIMILAR THREAD
\nThis is an instance segmentation problem.
\nFrom the above link…
\n\n\nInstance segmentation is the task of detecting AND delineating each distinct object of interest appearing in an image.
\n
Think of instance segmentation as Object Detection… except instead of identifying the bounding boxes for all instances, you are required to report the segmentation masks for all instances
", "rawMarkdown": "**COPYING FROM MY RESPONSE ON A SIMILAR THREAD**\n\n---\n\nThis is an [**instance segmentation**](https://paperswithcode.com/task/instance-segmentation/codeless) problem.\n\n*From the above link...*\n> Instance segmentation is the task of ***detecting AND delineating*** each distinct object of interest appearing in an image.\n\n* [**See here**](https://www.linkedin.com/pulse/quick-understanding-instance-segmentation-vs-semantic-rohan-chikorde/) for a nice post on it on Linkedin\n* See below for a visual representation of the differences between Object Detection, Semantic Segmentation (all instances are masked with the same pixel value), and Instance Segmentation (all instances are masked with their own respective value). \n * Notice how the two dogs are represented as different colours in the image... this is because they are different INSTANCES of the class dog.\n\n\n\n---\n\n**Think of instance segmentation as Object Detection... except instead of identifying the bounding boxes for all instances, you are required to report the segmentation masks for all instances**", "votes": null }, { "id": "1548066", "postDate": "10/17/2021 23:36:51", "content": "@saurabhbagchi - I'm not sure why but your link is redirecting me back to the discussion page of the Kaggle forum?
", "rawMarkdown": "saurabhbagchi - I'm not sure why but your link is redirecting me back to the discussion page of the Kaggle forum?", "votes": null }, { "id": "1548231", "postDate": "10/18/2021 05:25:26", "content": "Thanks for pointing out @dschettler8845 , have corrected it now.
", "rawMarkdown": "Thanks for pointing out @dschettler8845 , have corrected it now.", "votes": null } ], "comments": [ { "id": 1547730, "author_name": "saurabhbagchi", "author_url": "", "post_date": "10/17/2021 14:27:35", "content": "Below external link explains the concept beautifully, thanks @revathiprakash for initiating this topic
\n", "votes": null, "replies": [ { "id": 1548066, "author_name": "dschettler8845", "author_url": "", "post_date": "10/17/2021 23:36:51", "content": "@saurabhbagchi - I'm not sure why but your link is redirecting me back to the discussion page of the Kaggle forum?
", "votes": null, "replies": [] }, { "id": 1548231, "author_name": "saurabhbagchi", "author_url": "", "post_date": "10/18/2021 05:25:26", "content": "Thanks for pointing out @dschettler8845 , have corrected it now.
", "votes": null, "replies": [] } ] }, { "id": 1548065, "author_name": "dschettler8845", "author_url": "", "post_date": "10/17/2021 23:33:43", "content": "COPYING FROM MY RESPONSE ON A SIMILAR THREAD
\nThis is an instance segmentation problem.
\nFrom the above link…
\n\n\nInstance segmentation is the task of detecting AND delineating each distinct object of interest appearing in an image.
\n
Think of instance segmentation as Object Detection… except instead of identifying the bounding boxes for all instances, you are required to report the segmentation masks for all instances
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "1546332": "When we talk about Object Detection, we are here referring to identifying bounding boxes for different objects of our interest from the image. Bounding boxes are generally defined by the position of the top left corner (2 coordinates) and a width and height (in the number of pixels).\n \nwhereas Image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.\n\nPlease feel free to add more details on this.", "1547730": "Below external link explains the concept beautifully, thanks @revathiprakash for initiating this topic\n\nhttps://www.geeksforgeeks.org/object-detection-vs-object-recognition-vs-image-segmentation/#:~:text=Image%20segmentation%20is%20a%20further,object%20present%20in%20the%20image.", "1548065": "**COPYING FROM MY RESPONSE ON A SIMILAR THREAD**\n\n---\n\nThis is an [**instance segmentation**](https://paperswithcode.com/task/instance-segmentation/codeless) problem.\n\n*From the above link...*\n> Instance segmentation is the task of ***detecting AND delineating*** each distinct object of interest appearing in an image.\n\n* [**See here**](https://www.linkedin.com/pulse/quick-understanding-instance-segmentation-vs-semantic-rohan-chikorde/) for a nice post on it on Linkedin\n* See below for a visual representation of the differences between Object Detection, Semantic Segmentation (all instances are masked with the same pixel value), and Instance Segmentation (all instances are masked with their own respective value). \n * Notice how the two dogs are represented as different colours in the image... this is because they are different INSTANCES of the class dog.\n\n\n\n---\n\n**Think of instance segmentation as Object Detection... except instead of identifying the bounding boxes for all instances, you are required to report the segmentation masks for all instances**", "1548066": "saurabhbagchi - I'm not sure why but your link is redirecting me back to the discussion page of the Kaggle forum?", "1548231": "Thanks for pointing out @dschettler8845 , have corrected it now." }, "source": "meta" }