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onnx_model
Commit a68b5c32 authored by wangpeng's avatar wangpeng
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合并代码,去掉编译器的文件

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.gitignore
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...@@ -24,6 +24,7 @@ var/ ...@@ -24,6 +24,7 @@ var/
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*.egg *.egg
onnx_infer.egg-info
# Installer logs # Installer logs
pip-log.txt pip-log.txt
pip-delete-this-directory.txt pip-delete-this-directory.txt
...@@ -82,3 +83,4 @@ coverage_html/ ...@@ -82,3 +83,4 @@ coverage_html/
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onnx_infer/main.py
View file @ a68b5c32
# ******************* #*******************
""" """
this is the main which contain color and yolo this is the main which contain color and yolo
the color input need abs path of color.onnx and one image arr which generate from the croppic.py。 the color input need abs path of color.onnx and one image arr which generate from the croppic.py。
...@@ -6,9 +6,9 @@ the result is the color of the picture。 ...@@ -6,9 +6,9 @@ the result is the color of the picture。
the yolo is more complex, need, the path of anchor.txt, label.txt, and the image path， the yolo.onnx path the yolo is more complex, need, the path of anchor.txt, label.txt, and the image path， the yolo.onnx path
the result of this is the category and bounding box which is the max score. the result of this is the category and bounding box which is the max score.
""" """
# ******************* #*******************
from onnx_infer.yolodata import path2Img, letterbox_image, path2arr from onnx_infer.yolodata import letterbox_image, path2arr,arr2Img
from onnx_infer.onnx2kera import onnxinfere from onnx_infer.onnx2kera import onnxinfere
from onnx_infer.supression import Supress from onnx_infer.supression import Supress
import tensorflow as tf import tensorflow as tf
...@@ -21,18 +21,19 @@ categorys = ['long sleeve dress', 'vest dress', 'vest', 'long sleeve outwear', ' ...@@ -21,18 +21,19 @@ categorys = ['long sleeve dress', 'vest dress', 'vest', 'long sleeve outwear', '
class Main: class Main:
def __init__(self, colorOnnx_path, yoloOnnx_path, image_path): def __init__(self, colorOnnx_path, yoloOnnx_path, image_arr):
self.colorOnnx_path = colorOnnx_path self.colorOnnx_path = colorOnnx_path
self.yoloOnnx_path = yoloOnnx_path self.yoloOnnx_path = yoloOnnx_path
self.image_path = image_path self.image_arr = image_arr
self.score = 0.05 self.score = 0.05
self.iou = 0.05 self.iou = 0.05
self.picSize = (416, 416) self.picSize = (416, 416)
def bboxAndcategory(self): def bboxAndcategory(self):
bbox = [] bbox = []
category = [] category = []
image = path2Img(self.image_path) image = arr2Img(self.image_arr)
image_data = letterbox_image(image, self.picSize) image_data = letterbox_image(image, self.picSize)
precit = onnxinfere(self.yoloOnnx_path, image_data) precit = onnxinfere(self.yoloOnnx_path, image_data)
feature = [] feature = []
...@@ -47,7 +48,7 @@ class Main: ...@@ -47,7 +48,7 @@ class Main:
def colorAndbboxAndcategory(self): def colorAndbboxAndcategory(self):
bbox, category = self.bboxAndcategory() bbox, category = self.bboxAndcategory()
image_arr = path2arr(self.image_path) image_arr = self.image_arr
image_crop = cropImage(image_arr, bbox) image_crop = cropImage(image_arr, bbox)
resized = resize(image_crop) resized = resize(image_crop)
tmp = featureTransform(resized) tmp = featureTransform(resized)
...@@ -59,21 +60,21 @@ class Main: ...@@ -59,21 +60,21 @@ class Main:
colorOnnx_path = 'color.onnx' colorOnnx_path = 'color.onnx'
yoloOnnx_path = 'yolo3.onnx' yoloOnnx_path = 'yolo3.onnx'
def get_result(image_arr):
def get_result(image_path): m = Main(colorOnnx_path, yoloOnnx_path, image_arr)
m = Main(colorOnnx_path, yoloOnnx_path, image_path)
color, bbox, category = m.colorAndbboxAndcategory() color, bbox, category = m.colorAndbboxAndcategory()
return color, bbox, category return color, bbox, category
# if __name__ == '__main__': if __name__ == '__main__':
# colorOnnx_path = '/Users/apple/Desktop/color.onnx' colorOnnx_path = '/Users/apple/Desktop/color.onnx'
# image_path = '/Users/apple/Desktop/8.jpg' image_path = '/Users/apple/Desktop/8.jpg'
# yoloOnnx_path = '/Users/apple/Desktop/yolo3.onnx' yoloOnnx_path = '/Users/apple/Desktop/yolo3.onnx'
# m = Main(colorOnnx_path, yoloOnnx_path, image_path) m = Main(colorOnnx_path, yoloOnnx_path, image_path)
# color, bbox, category = m.colorAndbboxAndcategory() color, bbox, category = m.colorAndbboxAndcategory()
# print('its color is : {}, category is : {} '.format(color, category)) print('its color is : {}, category is : {} '.format(color, category))
# print('the bounding box is : {}'.format(bbox)) print('the bounding box is : {}'.format(bbox))
# print(color) # print(color)
# print(bbox) # print(bbox)
# print(category) # print(category)
onnx_infer/yolodata.py
View file @ a68b5c32
...@@ -12,6 +12,11 @@ def path2arr(path): ...@@ -12,6 +12,11 @@ def path2arr(path):
image = cv2.imread(path, cv2.IMREAD_COLOR) image = cv2.imread(path, cv2.IMREAD_COLOR)
return image return image
def arr2Img(image_arr):
image = Image.fromarray(image_arr)
return image
# this image is one Image type
def letterbox_image(image, size): def letterbox_image(image, size):
iw, ih = image.size iw, ih = image.size
h, w = size h, w = size
......
setup.py
View file @ a68b5c32
...@@ -33,3 +33,4 @@ setup( ...@@ -33,3 +33,4 @@ setup(
dependency_links=dependency_links, dependency_links=dependency_links,
author_email='Your address email (eq. you@example.com)' author_email='Your address email (eq. you@example.com)'
) )
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