def find_palms2(uid,fieldid, templateName):
    import pandas as pd
    import numpy as np
    import rasterio
    import matplotlib.pyplot as plt
    from scipy import ndimage as ndi
    from skimage.feature import peak_local_max
    from skimage import exposure
    import cv2
    templateName = 'template.png'


    filename = uid + '/highres_' +str(fieldid)+'.png'
    # loading the image - let's take a look at it
    img = cv2.imread(filename)
    #affine = img.transform
    p2, p98 = np.percentile(img, (2, 98))
    img_rescale = exposure.rescale_intensity(img, in_range=(p2, p98))
    image_max = ndi.maximum_filter(img, size=3, mode='constant')
    coordinates = peak_local_max(img, min_distance=2)
    X=coordinates[:, 1]
    y=coordinates[:, 0]

    #reproject data array into original dataset
    xs, ys = X, y

    # create some datasheet
    df = pd.DataFrame({'X':xs, 'Y':ys})

        # count trees
    count = df['X'].count()
    print('Total trees : {i}'.format(i = count))

    # also let's see how the countours are selected by plotting countours on the actual image.!!
    plt.axis('off')
    
    plt.imshow(img_rescale)
    #plt.show()
    fileName = uid +'/' + fieldid + '_highres_num.png'
    plt.savefig(fileName)
    return count