Update README.md

README.md

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 <!-- Provide a quick summary of what the model is/does. -->
 
-This repository contains a machine learning model trained for the purpose of detecting quail eggs in images. Leveraging the Quail Egg Detection Dataset, this model utilizes the YOLOv8 architecture, specifically the YOLOv8 Large variant from Ultralytics, known for its efficiency and accuracy in object detection tasks.
+This repository contains a machine learning model trained for the purpose of detecting quail eggs in images. 
 ## Model Details
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
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+Leveraging the Quail Egg Detection Dataset, this model utilizes the YOLOv8 architecture, specifically the YOLOv8 Large variant from Ultralytics, known for its efficiency and accuracy in object detection tasks.
 
 
 - **Developed by:** Jan Martens
@@ -24,171 +23,25 @@ This repository contains a machine learning model trained for the purpose of det
 
 ### Model Sources [optional]
 
-<!-- Provide the basic links for the model. -->
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+This model was trained using self-taken images in my henhouse and some additional ones in a classroom setting.
+The dataset can be found at "jan-martens0124/quail_egg"
 
 ## Uses
 
 Can be used to detect quail_eggs in a henhouse. It distingquisches quail_eggs from quails and other types of eggs.
 
-### Direct Use
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-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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-[More Information Needed]
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 ### Downstream Use [optional]
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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-[More Information Needed]
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-### Out-of-Scope Use
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-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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-[More Information Needed]
+When furhter trained, this model could be used to distinguish between different kind of eggs.
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+Sometimes, eastereggs with fancy packaging that has high-contrast silver paper are recognized as a quail egg. Also white chocolate eggs are often incorrectly identified.
 [More Information Needed]
 
-### Recommendations
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-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model.
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-[More Information Needed]
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-## Training Details
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-### Training Data
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-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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-[More Information Needed]
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-### Training Procedure
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-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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-#### Preprocessing [optional]
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-[More Information Needed]
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-#### Training Hyperparameters
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-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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-#### Speeds, Sizes, Times [optional]
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-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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-[More Information Needed]
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-## Evaluation
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-<!-- This section describes the evaluation protocols and provides the results. -->
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-### Testing Data, Factors & Metrics
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-#### Testing Data
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-<!-- This should link to a Dataset Card if possible. -->
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-[More Information Needed]
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-#### Factors
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-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-[More Information Needed]
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-#### Metrics
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-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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-[More Information Needed]
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-### Results
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-[More Information Needed]
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-#### Summary
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-## Model Examination [optional]
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-<!-- Relevant interpretability work for the model goes here -->
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-[More Information Needed]
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-## Environmental Impact
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-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
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-## Technical Specifications [optional]
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-### Model Architecture and Objective
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-[More Information Needed]
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-### Compute Infrastructure
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-[More Information Needed]
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-#### Hardware
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-[More Information Needed]
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-#### Software
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-[More Information Needed]
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-## Citation [optional]
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-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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-**BibTeX:**
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-[More Information Needed]
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-**APA:**
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-[More Information Needed]
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-## Glossary [optional]
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-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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-[More Information Needed]
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-## More Information [optional]
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-[More Information Needed]
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-## Model Card Authors [optional]
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-[More Information Needed]
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-## Model Card Contact
+You can use the code in the folder 'code' to get started with the model.
+The python-script detect_on_video_for_loop.py contains a script to let the model infer with your webcam or a video-file on your pc.
 
-[More Information Needed]