diff --git a/README_get_time_freq_detection.md b/README_get_time_freq_detection.md new file mode 100644 index 0000000000000000000000000000000000000000..12e3d350a9cb4fdb0c3404f1c23a49cff40f21f6 --- /dev/null +++ b/README_get_time_freq_detection.md @@ -0,0 +1,13 @@ + + +## Output (file.csv) of get_time_freq_detection.py + +| **_COLUMN NAME_** | **espece** | **conf** | **annot** | **midl** | **freq_center** | **freq_min** | **freq_max** | **start** | **stop** | **duration** | **station** | **site** | **date** | **date_t** | **normalized_hour** | +| ----------------: | -----------: | -----------: | -----------: | -----------: | --------------: | -----------: | -----------: | -----------: | -----------: | --------------: | -----------: | -----------: | --------: | ---------: | ------------------: | +| **_CLASS_** | vocalization | vocalization | vocalization | vocalization | vocalization | vocalization | vocalization | file | file | file | file | file | file | file | file | +| **_DESCRIPTION_** |label number ( ex : from 0 to 32 for 32 species labels) | confidence level of the prediction [value : 0-1] the higher it gets, the more confident the network get | name of species corresponding to « espece » column (ex : espece =0, annot = wtsp) | time when the vocalize is detected : (stop - start)/2 | centroid frequency of the detection (because the detection is inside a boundingbox : freq_center=height of the boundingbox/2) | minimum frequency of the boundingbox | maximal frequency of the vocalize | filename with the vocalize detected | filename with the vocalize detected | path to the file inside the server | sample frequency of the file with the vocalize | duration of the file with the vocalize (seconds) | station of the recordings | site name of the recordings | date of the recording with an hour precision | date of the recording without taking into acompt the hours | number of detections/hour of recording (ex: file duration=30min, normalized_hour=2) | + + + + +