Data for automated feed intake detection in European Seabass (Dicentrarchus labrax) with computer vision

The data contains videos, models, training datasets and results of the development to detect feed intake in European seabass. Averagely 20 grams European seabass reared in 3 different aquariums for 5 days. There are 10 fish in aquarium 1, 15 fish in aquarium 2 and 20 fish in aquarium 3. The aquarium are 240L in total volume but modified to have a green background and a slope at the bottom. Recording are done with two See3CAM_CU27 until apparent satiation. The models are trained to detect and tracked the pellets. When the pellet disappeared, it triggers a search proximity area and window to search for a confirming “open mouth” for a feeding action. If there is an "open mouth" detected, then feeding event is counted. The model folder contain the weights of the pellet detection model and the open mouth detection model (.pt or .onnx file) that can be used directly with a new input data. The video folder contain the raw input video of European seabass during feeding period and the output videos of the computer vision automatic detection of feed intake. The videos are representatives. One video per aquarium chosen by the largest number of feeding event detected for that particular aquarium. For access to all of the videos, contact the authors. The results are the csv files containing all of the recorded feed intake with headings: aquarium. The number of aquarium (1, 2 or 3) Day. Correspond to the date (24, 25, 26…) Feeding_Event_Id. The number of the feeding event per video Frame_Number. The number of the frame that the feeding event detected for the particular video Pellet_Disappearance_X. X coordinate of the last detection of the pellet Pellet_Disappearance_Y. Y coordinate of the last detection of the pellet Open_Mouth_X. X coordinate of the open mouth bounding box that confirmed the feeding event. Open_Mouth_Y. X coordinate of the open mouth bounding box that confirmed the feeding event. Open_Mouth_Confidence. The confidence of the particular open mouth detection that confirm the feeding event. Distance_Pellet_Mouth. The pixel distance from the pellet last detection to the open mouth bounding box of the feeding event Video_Filename. The video filename of the corresponding feeding event Pellet_Conf_Threshold. The confidence threshold for pellet detection. Open_Mouth_Conf_Threshold. The confidence threshold for open mouth detection. Proximity_Threshold. The proximity search for open mouth from the coordinate of the pellet last detection (in pixels). Pellet_Disappearance_Frames. Number of frames where a particular tracked pellet undetected for before considered disappeared. Open_Mouth_Detection_Window. A frame number where an open mouth is search for from the key frame where the pellet disappear. Min_Pellet_Detection_Frames. A minimum number of frame to validate a pellet detection as a true pellet not just a debris. Priority_Area_Ratio. Ratio of a priority area on top of the video where pellet detection become valid immediately bypassing Min_Pellet_Detection_Frames Waste_Threshold_Y_Ratio. Ratio of the zone at the bottom of the video where pellet disappearance at that area will count as pellet waste. The training_datasets folder contains the annotated images and label to train the pellet detection and open mouth detection models.