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Update detect.py #1

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56 changes: 36 additions & 20 deletions detect.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,15 @@
"""
Usage:
$ python detect.py --model model_name --model_location model_path.pt --input_location image_path

model_name = [detr, ssd, fasterrcnn, yolov5, yolor, efficientdet]
if yolov5 you are in app/yolov5/:
model_path.pt & image_path should be relative paths


"""


import argparse
import cv2
import matplotlib.pyplot as plt
Expand All @@ -13,13 +25,11 @@
if __name__ == '__main__':
# intialize the parser
parser = argparse.ArgumentParser(
description='Predict using tick detection models'
)

description='Predict using tick detection models')
# arguments
parser.add_argument('--model', help='Model to use for tick object detection [detr, ssd, fasterrcnn, yolov5, yolor, efficientdet]')
parser.add_argument('--model_location' help='location of pretrained model')
parser.add_argument('--input_location', help='location of input')
parser.add_argument('--model', type=str, help='Model to use for tick object detection [detr, ssd, fasterrcnn, yolov5, yolor, efficientdet]')
parser.add_argument('--model_location', type=str, help='location of pretrained model')
parser.add_argument('--input_location', type=str, help='location of input image')
# parser.add_argument('--output_location', help='location of output')

# Parse the arguments
Expand All @@ -29,6 +39,7 @@
input_location = args.input_location
# output_location = args.output_location


if model=='detr':
first_class_index = 1
assert(first_class_index in [0, 1])
Expand Down Expand Up @@ -111,9 +122,9 @@
for path in paths.values():
if not os.path.exists(path):
if os.name == 'posix':
!mkdir -p {path}
os.mkdir(path)
if os.name == 'nt':
!mkdir {path}
os.mkdir(path)

import os
import tensorflow as tf
Expand All @@ -140,7 +151,7 @@ def detect_fn(image):
import cv2
import numpy as np
from matplotlib import pyplot as plt
%matplotlib inline
#%matplotlib inline

category_index = label_map_util.create_category_index_from_labelmap(files['LABELMAP'])

Expand Down Expand Up @@ -225,12 +236,17 @@ def detect_fn(image):


elif model=='yolov5':
!cd yolov5
!python detect.py --source image_location --weights model_location --conf-thres 0.5
import os
#yolov5_path = 'icarda_yolov_zip/icarda_yolov/app/yolov5'
yolov5_path = 'app/yolov5'
os.chdir(yolov5_path)
os.system('python detect.py --source ' + input_location + ' --weights ' + model_location)

elif model=='yolor':
!cd yolor
!python detect.py --source image_location --cfg cfg/yolor_p6.cfg --weights model_location --conf 0.5 --img-size 640 --device 0
import os
yolor_path = ''
os.chdi(yolor_path)
os.system('python detect.py --source '+ image_location +' --weights ' + model_location)

elif model=='efficientdet':
CUSTOM_MODEL_NAME = 'efficientdet'
Expand All @@ -255,11 +271,11 @@ def detect_fn(image):
}

for path in paths.values():
if not os.path.exists(path):
if os.name == 'posix':
!mkdir -p {path}
if os.name == 'nt':
!mkdir {path}
if not os.path.exists(path):
if os.name == 'posix':
os.mkdir(path)
if os.name == 'nt':
os.mkdir(path)

import os
import tensorflow as tf
Expand All @@ -286,7 +302,7 @@ def detect_fn(image):
import cv2
import numpy as np
from matplotlib import pyplot as plt
%matplotlib inline
#%matplotlib inline

category_index = label_map_util.create_category_index_from_labelmap(files['LABELMAP'])

Expand Down Expand Up @@ -325,4 +341,4 @@ def detect_fn(image):

else:
print('Model does not exist')