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file_name
stringclasses
4 values
quality
stringclasses
4 values
instrument_type
stringclasses
4 values
reading_value
stringclasses
4 values
reading_unit
stringclasses
4 values
display_text
stringclasses
4 values
reading_precision
stringclasses
4 values
brand_name
stringclasses
4 values
model_number
stringclasses
4 values
calibration_status
stringclasses
4 values
ambient_conditions
stringclasses
3 values
instrument_condition
stringclasses
3 values
5d1fb3e92685be13de19ad546c33bf98.jpg
2560*2061
Dial Indicator
3.0
mm
0.001mm
0.001mm
Unknown
Unknown
Unknown
Normal lighting
Intact
67a8c32a04166fb00a39093955ec4606.jpg
1080*1410
Pipette
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Normal lighting
Good
8457556b0a1ae52cbc24875a13b9b9c1.jpg
800*1172
caliper
approximately 3.9
cm
no digital display
0.05 mm
unknown
unknown
unknown
good
intact
9e5a7f0d2b225394fe186f271f125b7f.jpg
800*1041
Analytical Balance
0.0000
g
0.0000 g
0.1 mg
sartorius
BSA1245
Not Calibrated (Assumed, Standard Status)
Normal Indoor Lighting
Good

Scientific Laboratory Instrument Readout Recognition Dataset

In modern scientific research, laboratory instruments are key sources of data acquisition, while manual recording of instrument readouts is inefficient and prone to errors. Traditional solutions such as manual transcription and basic OCR technology often prove inadequate when dealing with complex backgrounds, reflections, and multiple fonts of scientific instrument readings. This dataset aims to solve the problem of automatic recognition of diverse instrument readings in complex environments, improving the accuracy and efficiency of scientific work. The data is captured using high-resolution camera equipment under standard laboratory lighting conditions, and has undergone multiple rounds of quality inspection, including expert verification and consistency checks, ensuring the reliability of the data. The annotation team is composed of 20 professionals with backgrounds in physics, chemistry, and biology. The data undergoes pre-processing steps such as segmentation, normalization, and various noise treatments, stored in JPEG format, and is structured for quick access. The dataset achieves 99% accuracy in annotation and consistency better than 95%, ensuring data integrity. Advanced image pre-processing and improved OCR algorithms are used to enhance data parsing accuracy. It effectively solves the problem of manual data entry for scientific research, improving readout entry speed by over 50%. Compared with other datasets, it covers more instrument types and scenarios, with a rarity in optical character challenges, suitable for a wide range of scientific fields. It has good scalability and can be used in other fields such as industrial equipment readouts.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
instrument_type string Identifies the type of instrument in the image, such as microscope or spectrometer.
reading_value float The instrument reading displayed in the image, such as temperature or concentration.
reading_unit string The unit of the instrument reading shown in the image, such as Celsius or Pascal.
display_text string The text or numerical content displayed on the instrument's screen.
reading_precision float The precision or error range of the instrument reading shown in the image.
brand_name string Identifies the brand name of the instrument in the image.
model_number string Identifies the model number of the instrument in the image.
calibration_status string The calibration status of the instrument in the image, such as calibrated or uncalibrated.
ambient_conditions string The ambient conditions at the time the image was taken, like lighting and humidity.
instrument_condition string The physical condition of the instrument in the image, such as intact or damaged.

Compliance Statement

Authorization Type CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial Use Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization No PII, no real company names, simulated scenarios follow industry standards
Compliance System Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com

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