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Commit b1328a0b authored by Stephane Chavin's avatar Stephane Chavin
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## 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) |
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