Object-Detection | Tracking | Counting

Frame Generation

1. Run Frame_generation/frame_generation_kaggle.ipynb on kaggle
2. get generated folder link at the end and copy it
3. using kaglle_to_colab_to_drive.ipynb on colab unzip and upload them (generated frames) directly to the google drive

Anotation

1. Using Frame_anotation/drive_to_colab_to_roboflow.ipynb upload frames from google drive to roboflow
2. Anotate them using Roboflow

Object Detection

1. Add custom dataset snipest from roboflow
2. Run Object_detection/object_detection_kaggle.ipynb on kaggle
3. get generated folder links at the end and copy them
4. using kaglle_to_colab_to_drive.ipynb on colab unzip and upload them (trained models) directly to the google drive

Track Objects and Count

1. Run Track_and_count/track_and_count_kaggle.ipynb on kaggle
2. get generated file link at the end and copy it
3. using kaglle_to_colab_to_drive.ipynb on colab copy and upload them (output video) directly to the google drive

Pose Estimation on human hands

1. Run Pose-estimation/pose-estimation-kaggle.ipynb on kaggle
2. get generated file link at the end and copy it
3. using kaglle_to_colab_to_drive.ipynb on colab copy and upload them (output video) directly to the google drive

Segmentation on boxes

1. Run Segmentation/segmentation-model-kaggle.ipynb on kaggle
2. get generated file link at the end and copy it
3. using kaglle_to_colab_to_drive.ipynb on colab copy and upload them (output video) directly to the google drive