LabPics Dataset

The dataset contains 8000 annotated images for both liquid and solid materials the vessels containing them in chemistry labs, medical labs, and any area where liquids and solids are handled within containers. There are two levels of annotation for each image. One annotation set for vessels and the second for the materials inside these vessels. The segmentation include semantic level segmentation (vessel, liquid, solid, filled, foam...) and instance segmentation where every container or material phase is seperate segment. For example, for two-phase separating liquids, each liquid phase is annotated as one instance. Vessels are defined as any container that can carry materials such as Jars, Erlenmayers, Tubes, Funnels, syringes, IV bags, and any other labware or glassware that can contain or carry materials. Material phases are any material contained within or on the vessel.

If there is foam above the liquid or a chunk of solid inside the liquid, the foam, liquid, and solid will be annotated as different phases (different segments), similarly for phase separating liquids, each liquid phase is annotated as one instance. In addition, vessel parts like cork, labels, and valves are annotated as instances. For each instance, there is a list of all the classes it belongs to, and a list of its property. For vessels, the instance classes are the vessel type (Cup, jar, Separatory-funnel…) and the vessel properties (Transparent, Opaque…). For materials, the classes are the material types ( Liquid, solid, suspension, foam, powder…) and their properties (Scattered, On vessel surface…), and for parts, the part type (cork/label). In addition, the relations between instances are annotated. This includes which materials instances are inside which vessels, which vessels are linked to each other or are inside each other (for vessels inside other vessels), and which material phase is immersed inside another material phase (for solid inside liquid). In addition to instance segmentation maps, the dataset also includes semantic segmentation maps that give for each pixel in the image all the classes to which it belongs. In other words, for each class (Liquid, Solid, Vessel, Foam), there is a map of all the regions in the image belonging to this class. Note that every pixel and every instance can have several classes. In addition, instances often overlap, like in the case of material inside the vessel, vessel inside the vessel, and material phase immerse inside other material (like solid chunk inside liquid).

Files:

LabPicsChemistry.zip 6000 LabPics2 annotated images chemistry lab and everyday liquid handling.

LabPicsMedical.zip 2000 LabPics2 annotated images medical labs and hospitals

LabPicsV1.zip 3K images chemistry lab and everyday liquid handling. (LabPics1 original version smaller and less detailed but simpler and easier to use)

Papers:

LabpicsV1: Computer Vision for Recognition of Materials and Vessels in Chemistry Lab Settings and the Vector-LabPics Data Set

LabPicsV2: Computer vision for liquid samples in hospitals and medical labs using hierarchical image segmentation and relations prediction

Catagories:

Materials Classes: Liquid, Foam, Suspension, Solid, Powder, Urine, Blood, Gel, Granular, SolidLargChunk, Vapor, Other Material, Filled

Material Properties: Material On vessel Surface, Material Scattered, Material Immersed Inside other material

Vessel/Container/Plates Classes: Vessel, Syringe, Pipette, Tube, IVBag, DripChamber, IVBottle, Beaker, RoundFlask, Cylinder, SeparatoryFunnel, Funnel, Burete, ChromatographyColumn, Condenser, Bottle, Jar, Connector, Flask, Cup, Bowl, Erlenmeyer, Vial, Dish, HeatingVessel, Tube

Vessel Properties: Transparent, SemiTrans, Opaque, DisturbeView, VesselInsideVessel

Vessels Parts Classes:Cork, Label, Part, Spike, Valve, Magnetic Stirrer, Thermometer, Spatula, Holder, Filter, Pipe/Tube/Straw

Semantic Segmentation

Instance Segmentation

Relations Annotations