Image Size Chart
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Image Sensor | Image Circle | Horizontal | Vertical |
1/4' | Ø4.0mm | 3.2mm | 2.4mm |
1/3' | Ø6.0mm | 4.8mm | 3.6mm |
1/2' | Ø8.0mm | 6.4mm | 4.8mm |
2/3' | Ø11.0mm | 8.8mm | 6.6mm |
1' | Ø16.0mm | 12.8mm | 9.6mm |
Image Size
Image Sensor Size (units in mm)
Image Size
A lens produces images in the form of a circle, called the image circle. In a CCTV camera, the imaging element has a rectangular sensor area (the image size) that detects the image produced within the image circle. The ratio of the length of the horizontal to vertical sides of a video image is called the aspect ratio, which is normally 4:3 (H:V) for a standard CCTV camera.
Relationship Between Angle of View and Image Sensor Size
An important factor to remember is that cameras with different image sensor chip sizes (such as 1/4', 1/3', 1/2', 2/3' and 1'), using the same focal length lens, will each yield a different field of view.
Lenses designed for a larger image sensor device will work on a new, smaller size camera. However, if a lens designed for a smaller format image sensor device (ie. 1/3') is placed on a larger one (ie. 2/3'), the image on the monitor will have dark corners.
Image sensor sizes are in a ratio of 1:0.69:0.5:0.38:0.25. This means that a 1/2' format is 50% of a 1' format, a 1/2' format is 75% of a 2/3' format and a 1/3' format is 75% of a 1/2' format.
Minimum Object Distance
Minimum object distance (M.O.D.) indicates how close the lens can be placed to the object for shooting. It is measured from the vertex of the front glass of the lens.
Flange Distance and Back Focal Length
Distance between mechanical mount surface and the image sensor (in air).
C-Mount=17.526 mm / .690'
CS-Mount=12.526 mm / .492'
C-Mount=17.526 mm / .690'
CS-Mount=12.526 mm / .492'
Back Focal Length
Distance between vertex of the rear element lens and image sensor.
C-Mount and CS-Mount Lens Compatibility
Compatibility | C-Mount Camera | CS-Mount Camera |
C-Mount Lens | OK | OK |
CS-Mount Lens | NO | OK |
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Angle of View and Field of View
Angle of View |
The angle of view is the shooting range that can be viewed by the lens given a specified image size. It is usually expressed in degrees. Normally the angle of view is measured assuming a lens is focused at infinity. The angle of view can be calculated if the focal length and image size are known. If the distance of the object is finite, the angle is not used. Instead, the dimension of the range that can actually be shot, or the field of view, is used.
Focal Length
Parallel incident light transmitted into a convex lens converges to a point on the optical axis. This point is the focal point of the lens. The distance between the principle point in the optical system and the focal point is referred to as the focal length. For a single thin lens, the focal length is equal to the distance between the center of the lens and the focal point.
Zoom Ratio
Zoom ratio is the ratio of the focal length at the telephoto end to that at the wide end. A zoom lens can change the size of an object appearing on the monitor to the extent specified by the zoom ratio
Zoom ratio is the ratio of the focal length at the telephoto end to that at the wide end. A zoom lens can change the size of an object appearing on the monitor to the extent specified by the zoom ratio
You are viewing the downloads of the latest version of Open Images (V6 - released Feb 2020), if you would like to view the downloads of previous versions, please select it here:
Subset with Bounding Boxes (600 classes), Object Segmentations, Visual Relationships, and Localized Narratives
These annotation files cover the 600 boxable object classes, and span the 1,743,042 training images where we annotated bounding boxes, object segmentations, visual relationships, and localized narratives; as well as the full validation (41,620 images) and test (125,436 images) sets.Trouble downloading the pixels? Let us know.
Subset with Image-Level Labels (19,958 classes)
These annotation files cover all object classes. In the train set, the human-verified labels span 7,337,077 images, while the machine-generated labels span 8,949,445 images. The image IDs below list all images that have human-verified labels. The annotation files span the full validation (41,620 images) and test (125,436 images) sets.Trouble downloading the pixels? Let us know.
Complete Open Images
The full set of 9,178,275 images.Trouble downloading the pixels? Let us know.
Open Images Extended
Data Formats
Bounding boxes
Each row defines one bounding box.
ImageID
: the image this box lives in.Source
: indicates how the box was made:xclick
are manually drawn boxes using the method presented in [1], were the annotators click on the four extreme points of the object. In V6 we release the actual 4 extreme points for all xclick boxes in train (13M), see below.activemil
are boxes produced using an enhanced version of the method [2]. These are human verified to be accurate at IoU>0.7.
LabelName
: the MID of the object class this box belongs to.Confidence
: a dummy value, always 1.XMin
,XMax
,YMin
,YMax
: coordinates of the box, in normalized image coordinates. XMin is in [0,1], where 0 is the leftmost pixel, and 1 is the rightmost pixel in the image. Y coordinates go from the top pixel (0) to the bottom pixel (1).XClick1X
,XClick2X
,XClick3X
,XClick4X
,XClick1Y
,XClick2Y
,XClick3Y
,XClick4Y
: normalized image coordinates (asXMin
, etc.) of the four extreme points of the object that produced the box using [1] in the case ofxclick
boxes. Dummy values of -1 in the case ofactivemil
boxes.
The attributes have the following definitions:
IsOccluded
: Indicates that the object is occluded by another object in the image.IsTruncated
: Indicates that the object extends beyond the boundary of the image.IsGroupOf
: Indicates that the box spans a group of objects (e.g., a bed of flowers or a crowd of people). We asked annotators to use this tag for cases with more than 5 instances which are heavily occluding each other and are physically touching.IsDepiction
: Indicates that the object is a depiction (e.g., a cartoon or drawing of the object, not a real physical instance).IsInside
: Indicates a picture taken from the inside of the object (e.g., a car interior or inside of a building).
![Image Image](https://i.pinimg.com/736x/c8/d4/c8/c8d4c88e1e2a08a30d87e93e3f0d791f.jpg)
For each of them, value
1
indicates present, 0
not present, and -1
unknown.Instance segmentation masks
The masks information is stored in two files:
- Individual mask images, with information encoded in the filename.
- A comma-separated-values (CSV) file with additional information (
masks_data.csv
).
The masks images are PNG binary images, where non-zero pixels belong to a single object instance and zero pixels are background. The file names look as follows (random 5 examples):
The format of .zip archives names is the following: each
The value of
<subset>_<suffix>.zip
contains all masks for all images with the first characted of ImageID equal to <suffix>
.The value of
<suffix>
is from 0-9 and a-f.Each row in
masks_data.csv
describes one instance, using similar conventions as the boxes CSV data file. Music paradise player 1 0 2.MaskPath
: name of the corresponding mask image.ImageID
: the image this mask lives in.LabelName
: the MID of the object class this mask belongs to.BoxID
: an identifier for the box within the image.BoxXMin
,BoxXMax
,BoxYMin
,BoxYMax
: coordinates of the box linked to the mask, in normalized image coordinates. Note that this is not the bounding box of the mask, but the starting box from which the mask was annotated. These coordinates can be used to relate the mask data with the boxes data.PredictedIoU
: if present, indicates a predicted IoU value with respect to ground-truth. This quality estimate is machine-generated based on human annotator behaviour. See [3] for details.Clicks
: if present, indicates the human annotator clicks, which provided guidance during the annotation process we carried out (See [3] for details). This field is encoded using the following format:X1 Y1 T1;X2 Y2 T2;X3 Y3 T3;..
.Xi Yi
are the coordinates of the click in normalized image coordinates.Ti
is the click type, value0
indicates the annotator marks the point as background, value1
as part of the object instance (foreground). These clicks can be interesting for researchers in the field of interactive segmentation. They are not necessary for users interested in the final masks only.
Visual relationships
Each row in the file corresponds to a single annotation.
Small Image 2 4 0t
ImageID
: the image this relationship instance lives in.LabelName1
: the label of the first object in the relationship triplet.XMin1,XMax1,YMin1,YMax1
: normalized bounding box coordinates of the bounding box of the first object.LabelName2
: the label of the second object in the relationship triplet, or an attribute.XMin2
,XMax2
,YMin2
,YMax2
: If the relationship is between a pair of objects: normalized bounding box coordinates of the bounding box of the second object. For an object-attribute relationship (RelationLabel='is'): normalized bounding box of the first object (repeated). In this case, LabelName2 is an attribute.RelationLabel
: the label of the relationship ('is' in case of attributes).
Image Labels
Human-verified and machine-generated image-level labels:
Small Image 2 4 0 X 2
Source
: indicates how the annotation was created:verification
are labels verified by in-house annotators at Google.crowdsource-verification
are labels verified from the Crowdsource app.machine
are machine-generated labels.
Confidence
: Labels that are human-verified to be present in an image have confidence = 1 (positive labels). Labels that are human-verified to be absent from an image have confidence = 0 (negative labels). Machine-generated labels have fractional confidences, generally >= 0.5. The higher the confidence, the smaller the chance for the label to be a false positive.Class Names
The class names in MID format can be converted to their short descriptions by looking into
class-descriptions.csv
:Note the presence of characters like commas and quotes. The file follows standard CSV escaping rules. e.g.:
Image IDs
It has image URLs, their OpenImages IDs, the rotation information, titles, authors, and license information:
Small Image 2 4 0 Cm
Each image has a unique 64-bit ID assigned. In the CSV files they appear as zero-padded hex integers, such as
000060e3121c7305
.The data is as it appears on the destination websites.
OriginalSize
is the download size of the original image.OriginalMD5
is base64-encoded binary MD5, as described here.Thumbnail300KURL
is an optional URL to a thumbnail with ~300K pixels (~640x480). It is provided for the convenience of downloading the data in the absence of more convenient ways to get the images. If missing,OriginalURL
must be used (and then resized to the same size, if needed). These thumbnails are generated on the fly and their contents and even resolution might be different every day.Rotation
is the number of degrees that the image should be rotated counterclockwise to match the Flickr user intended orientation (0
,90
,180
,270
).nan
means that this information is not available. Check this announcement for more information about the issue.
Hierarchy for 600 boxable classes
Small Image 2 4 0 4
View the set of boxable classes as a hierarchy here or download it as a JSON file:
References
- 'Extreme clicking for efficient object annotation', Papadopolous et al., ICCV 2017. Mach desktop 3 0 1.
- 'We don't need no bounding-boxes: Training object class detectors using only human verification, Papadopolous et al., CVPR 2016.
- 'Large-scale interactive object segmentation with human annotators', Benenson et al., CVPR 2019.