def draw_row(canvas:Canvas, row:tuple, top_left:tuple, pixel:int=25):
x = top_left[0]
y = top_left[1]
# you could also make a palette and each cell number
# could access a color in the palette:
palette = [None, '#E0607E', 'black', 'white']
for cell in row:
if cell != 0:
fill = palette[cell]
make_square(canvas, (x, y), pixel, fill_color=fill)
x += pixel
def run_inference(inf_file):
# Preprocessing of the image happens here
img = load_image(inf_file)
print("Image Loaded")
img = make_square(img)
img = augment(prep, img)
print("Transformations done")
img = img.transpose(-1, 0, 1).astype(np.float32)
img = img.reshape(-1, CHANNELS, IMG_WIDTH, IMG_HEIGHT)
# Inferencing starts here
sess = onnxruntime.InferenceSession("./best_acc.onnx")
print("The model expects input shape: ", sess.get_inputs()[0].shape)
print("The shape of the Image is: ", img.shape)
input_name = sess.get_inputs()[0].name
result = sess.run(None, {input_name: img})
prob_array = result[0][0]
print("Prob Array ", prob_array)
prob = max(softmax(result[0][0]))
print("Prob ", prob)
species = tf.argmax(prob_array.ravel()[:10]).numpy()
print("Class Label ", species)
print("Spec ", CLASS_MAP[species][1])
string_label = CLASS_MAP[species][1].split(" ")
return (string_label[0], string_label[1], str(prob), color_code(prob))
def draw_row(canvas:Canvas, row:tuple, top_left:tuple, pixel:int=25):
x = top_left[0]
y = top_left[1]
for cell in row:
if cell == 1:
make_square(canvas, (x, y), pixel, fill_color='#E0607E')
elif cell == 2:
make_square(canvas, (x, y), pixel, fill_color='black')
elif cell == 3:
make_square(canvas, (x, y), pixel, fill_color='white')
x += pixel
def run_inference(inf_file):
# Preprocessing of the image happens here
img = load_image(inf_file)
originalimg = img
#Cropping line is below, SHOULD NOT BE INCLUDED IN THIS VERSION
#useless, img, status=cropImage(impath, 'm', labelsfile, 21, 0.08)
print("Image Loaded")
img = make_square(img)
img = augment(prep, img)
print("Transformations done")
img = img.transpose(-1, 0, 1).astype(np.float32)
img = img.reshape(-1, CHANNELS, IMG_WIDTH, IMG_HEIGHT)
# Inferencing starts here
sess = onnxruntime.InferenceSession("./best_acc.onnx")
print("The model expects input shape: ", sess.get_inputs()[0].shape)
print("The shape of the Image is: ", img.shape)
input_name = sess.get_inputs()[0].name
result = sess.run(None, {input_name: img})
prob_array = result[0][0]
print("Prob Array ", prob_array)
prob = max(softmax(result[0][0]))
print("Prob ", prob)
species = tf.argmax(prob_array.ravel()[:20]).numpy()
print("Class Label ", species)
print("Spec ", CLASS_MAP[species][1])
string_label = CLASS_MAP[species][1].split(" ")
#fullfilename = mosquitoid + "_" + picnum + "_" + string_label[0] + "_" + string_label[1]
#fullbucket = 'photostakenduringpilotstudy'
#s3_file = 'PilotStudy'
#file = cv2.imwrite(fullfilename, originalimg)
#upload_to_aws(file, fullbucket , s3_file)
##upload_file(file, fullbucket)
return (string_label[0], string_label[1], str(prob), color_code(prob))
# value of your y coordinate as shown below.
#
# Now, how could you convert the program below to a function so that you
# could create multiple frankensteins drawn at different sizes, colors, and
# position?
# frankenstein anchored at position (x, y)
pixel = 20
top_left = (100, 50)
body_color = '#5ec031'
pants_color = 'hotpink'
x = top_left[0]
y = top_left[1]
# row 1
make_square(canvas, (x + 2 * pixel, y), pixel, fill_color='black')
make_square(canvas, (x + 3 * pixel, y), pixel, fill_color='black')
make_square(canvas, (x + 4 * pixel, y), pixel, fill_color='black')
make_square(canvas, (x + 5 * pixel, y), pixel, fill_color='black')
make_square(canvas, (x + 6 * pixel, y), pixel, fill_color='black')
# row 2
make_square(canvas, (x + 2 * pixel, y + pixel), pixel, fill_color=body_color)
make_square(canvas, (x + 3 * pixel, y + pixel), pixel, fill_color=body_color)
make_square(canvas, (x + 4 * pixel, y + pixel), pixel, fill_color=body_color)
make_square(canvas, (x + 5 * pixel, y + pixel), pixel, fill_color=body_color)
make_square(canvas, (x + 6 * pixel, y + pixel), pixel, fill_color=body_color)
# row 3
make_square(canvas, (x + 2 * pixel, y + 2 * pixel),
pixel,
from itertools import product
import matplotlib.pyplot as plt
from neupy import algorithms, utils, init
from helpers import plot_2d_grid, make_circle, make_elipse, make_square
plt.style.use('ggplot')
utils.reproducible()
if __name__ == '__main__':
GRID_WIDTH = 4
GRID_HEIGHT = 4
datasets = [
make_square(),
make_circle(),
make_elipse(corr=0.7),
]
configurations = [{
'weight_init': init.Uniform(0, 1),
'title': 'Random uniform initialization',
}, {
'weight_init': 'sample_from_data',
'title': 'Sampled from the data',
}, {
'weight_init': 'init_pca',
'title': 'Initialize with PCA',
}]
plt.figure(figsize=(15, 15))
# Note that each of the x-positions can be re-written in terms of
# the pixel value. The advantage of rewriting your code in this
# way is that it allows you to be able to scale your frankenstein.
# In other words, if you update the size of the pixel (using the
# pixel variable below), the monster scales.
# However, no matter what, frankenstein is still anchored at
# position (0, 0). How could you alter this program so that frank
# could be drawn *anywhere on the screen?
pixel = 25
body_color = '#5ec031'
pants_color = 'hotpink'
# row 1 # before:
make_square(canvas, (2 * pixel, 0), pixel, fill_color='black') # (50, 0), 25
make_square(canvas, (3 * pixel, 0), pixel, fill_color='black') # (75, 0), 25
make_square(canvas, (4 * pixel, 0), pixel, fill_color='black') # (100, 0), 25
make_square(canvas, (5 * pixel, 0), pixel, fill_color='black') # (125, 0), 25
make_square(canvas, (6 * pixel, 0), pixel, fill_color='black') # (150, 0), 25
# row 2
make_square(canvas, (2 * pixel, pixel), pixel,
fill_color=body_color) # (50, 25), 25
make_square(canvas, (3 * pixel, pixel), pixel,
fill_color=body_color) # (75, 25), 25
make_square(canvas, (4 * pixel, pixel), pixel,
fill_color=body_color) # (100, 25), 25
make_square(canvas, (5 * pixel, pixel), pixel,
fill_color=body_color) # (125, 25), 25
make_square(canvas, (6 * pixel, pixel), pixel,
def draw_row(canvas: Canvas, row: tuple, top_left: tuple, pixel: int = 25):
x = top_left[0]
y = top_left[1]
for cell in row:
make_square(canvas, (x, y), pixel, fill_color='grey')
x += pixel
from helpers import make_square, make_grid # initialize window gui = Tk() canvas = Canvas(gui, width=600, height=600, background='white') canvas.pack() ########################## YOUR CODE BELOW THIS LINE ############################## # helper function that draws a grid. make_grid(canvas, 600, 600) body_color = '#5ec031' # row 1 make_square(canvas, (50, 0), 25, fill_color='black') # pixel (3, 1) make_square(canvas, (75, 0), 25, fill_color='black') # pixel (4, 1) make_square(canvas, (100, 0), 25, fill_color='black') # pixel (5, 1) make_square(canvas, (125, 0), 25, fill_color='black') # pixel (6, 1) make_square(canvas, (150, 0), 25, fill_color='black') # pixel (7, 1) # row 2 make_square(canvas, (50, 25), 25, fill_color=body_color) # pixel (3, 2) make_square(canvas, (75, 25), 25, fill_color=body_color) # pixel (4, 2) make_square(canvas, (100, 25), 25, fill_color=body_color) # pixel (5, 2) make_square(canvas, (125, 25), 25, fill_color=body_color) # pixel (6, 2) make_square(canvas, (150, 25), 25, fill_color=body_color) # pixel (7, 2) # row 3 make_square(canvas, (50, 50), 25, fill_color=body_color) # pixel (3, 3) make_square(canvas, (75, 50), 25, fill_color=body_color) # pixel (4, 3)