Feature-level dual-light detection fusion development and equipment adaptation services
For enterprise R&D, equipment manufacturers and system integration projects that use "synchronous dual light and annotation", it provides demand assessment, algorithm implementation, interface packaging, target platform adaptation and independent test design, with "target results and modal weights" as the agreed output.
Service scope and project output
Target results and modal weights
This project belongs to special model development. It is necessary to confirm the target category, data collection and labeling rules, training and independent test sets, deployment platform and rejection requirements, and then determine the model structure and acceptance threshold.
Implementation route
- Data and interface verificationConfirm input format, bit depth, timestamp, camera parameters, target platform and exception frame rules.
- Baseline and project implementationEstablish a reviewable baseline, and then implement the core algorithm according to the target object, physical conditions and indicators.
- quality gatingOutput validity, confidence, failure reasons and logs, and do not replace exception handling with unconditional results.
- Integration and retestingEncapsulate the interface and retest accuracy, latency and resource usage on the target platform and independent test sets.
Information required before assessment
Algorithm specific input: synchronized dual light and annotation.
- Camera model, spectral band, resolution, lens, distance, field of view and SDK/data format
- Original samples without screenshots, compression or pseudo-color changes, as well as normal, abnormal and failure conditions
- Target object, minimum size, temperature/reflective properties, environment and device loading information
- Reference truth values, annotation specifications, independent test sets, and written passing thresholds
- Target hardware, operating system, call interface, ticks, memory and power constraints
- Source code, model weights, third-party dependencies, number of deployments, and maintenance scope requirements
Delivery content and interface agreement
The delivery of "target results and modal weights" and their quality status can be agreed upon, and the file format and interface specifications are confirmed in the project plan.
- Requirements and technical solutions, input and output and interface field definitions
- Algorithm library, model or SDK/API; delivery form is confirmed in the project plan
- Sample program, parameter configuration, error status and calling instructions
- Test set version, indicator definition, stratification results and failed sample records
- Target platform adaptation, resource usage and running delay records
- Version, dependencies, license, reproduction steps and applicable conditions description
Acceptance methods and indicators
Freeze categories, annotations, independent test sets and thresholds, and report Recall, Precision, Macro-F1, false positive rate, rejection results and failed samples for each category hierarchically by scenario.
Fix code, model/weights, parameters, dependencies, target platform, data version and statistical scripts before acceptance. Results are stratified by critical conditions and failure samples are provided; conditions not covered are listed as limitations and are not combined into the overall mean.
Acceptance thresholds are written into the project plan after sample evaluation and confirmed together with test data, target platform and statistical methods.
Implementation and Procurement Phase
- Project input confirmationCheck camera, spectral band, bit depth, SDK, environmental conditions, sample and acceptance true value.
- Sample verificationVerify key processing links, applicable conditions and abnormal working conditions, and determine the development scope and acceptance methods.
- Algorithm development and integrationImplement data parsing, algorithms, quality gating, interfaces and target platform deployment.
- Test acceptance and handoverRetest according to the agreed test set and target platform, and hand over the deliverables, test results and applicable conditions.
Applicable boundaries and authorization
This project belongs to special model development. It is necessary to confirm the target category, data collection and labeling rules, training and independent test sets, deployment platform and rejection requirements, and then determine the model structure and acceptance threshold.
Commercial licenses for input data, third-party code, model weights, and training data are checked on a case-by-case basis. The usage scope, storage method and access rights of customer data are agreed upon by the project; the deployment quantity, source code scope, maintenance period and on-site responsibilities are specified in the project plan.
Common project questions
Can this algorithm be deployed to existing equipment?
It is necessary to first check the camera data interface, target platform, computing power, memory, operating system and calling method, and complete device interface joint debugging and target working condition testing.
What samples are required?
At least provide original normal, abnormal and failure condition samples, and retain camera parameters, environment, load, timestamp and reference measurements. Only when screenshots are shown, the range of conclusions they can support should be made clear.
How to arrange project acceptance?
Freeze categories, annotations, independent test sets and thresholds, and report Recall, Precision, Macro-F1, false positive rate, rejection results and failed samples for each category hierarchically by scenario.
How to evaluate cost and cycle time?
First split the work package according to sample verification, special development, interface packaging, target platform adaptation and independent acceptance. Data preparation, physical calibration, third-party licensing, source code scope and on-site joint debugging will affect the cycle time and quotation.
Define the Development Scope with Samples and Device Requirements
Feature-level dual-light detection fusion development and equipment adaptation services
Please describe the task object, original picture or video, target indicators, device platform, interface and sample situation.
Phone: 13910119357xuzhiyang0928@gmail.com