birdCLEF_spec.py 文件源码

def hasBird(spec, threshold=16):

    #working copy
    img = spec.copy()

    #STEP 1: Median blur
    img = cv2.medianBlur(img,5)

    #STEP 2: Median threshold
    col_median = np.median(img, axis=0, keepdims=True)
    row_median = np.median(img, axis=1, keepdims=True)

    img[img < row_median * 3] = 0
    img[img < col_median * 4] = 0
    img[img > 0] = 1

    #STEP 3: Remove singles
    img = filter_isolated_cells(img, struct=np.ones((3,3)))

    #STEP 4: Morph Closing
    img = cv2.morphologyEx(img, cv2.MORPH_CLOSE, np.ones((5,5), np.float32))

    #STEP 5: Frequency crop
    img = img[128:-16, :]

    #STEP 6: Count columns and rows with signal
    #(Note: We only use rows with signal as threshold, but columns might come in handy in other scenarios)

    #column has signal?
    col_max = np.max(img, axis=0)
    col_max = ndimage.morphology.binary_dilation(col_max, iterations=2).astype(col_max.dtype)
    cthresh = col_max.sum()

    #row has signal?
    row_max = np.max(img, axis=1)
    row_max = ndimage.morphology.binary_dilation(row_max, iterations=2).astype(row_max.dtype)
    rthresh = row_max.sum()

    #final threshold
    thresh = rthresh

    #DBUGB: show?
    #print thresh
    #cv2.imshow('BIRD?', img)
    #cv2.waitKey(-1)

    #STEP 7: Apply threshold (Default = 16)
    bird = True
    if thresh < threshold:
        bird = False

    return bird, thresh

######################################################

#elist all bird species