package

onnx_infer.egg-info/PKG-INFO

+Metadata-Version: 1.0
+Name: onnx-infer
+Version: 0.1.0
+Summary: model inference
+Home-page: http://git.wanmeizhensuo.com/wujilong/onnx_model.git
+Author: wjl
+Author-email: wujilong@igengmei.com
+License: MIT
+Description: UNKNOWN
+Platform: UNKNOWN

onnx_infer.egg-info/SOURCES.txt

+setup.py
+onnx_infer/__init__.py
+onnx_infer/color.py
+onnx_infer/croppic.py
+onnx_infer/drawpic.py
+onnx_infer/main.py
+onnx_infer/onnx2kera.py
+onnx_infer/supression.py
+onnx_infer/yolodata.py
+onnx_infer.egg-info/PKG-INFO
+onnx_infer.egg-info/SOURCES.txt
+onnx_infer.egg-info/dependency_links.txt
+onnx_infer.egg-info/top_level.txt
+onnx_infer/yolo3/__init__.py
+onnx_infer/yolo3/model.py
+onnx_infer/yolo3/utils.py
\ No newline at end of file

onnx_infer.egg-info/dependency_links.txt

+

onnx_infer.egg-info/top_level.txt

+onnx_infer

onnx_infer/color.py

-from onnx2kera import onnxinfere
+from .onnx2kera import onnxinfere
 import numpy as np
 import cv2
 from copy import deepcopy

onnx_infer/croppic.py

@@ -9,7 +9,7 @@ def saveCrop(image, savePath):
     cv2.imwrite(savePath, image)
 
 if __name__ == '__main__':
-    from yolodata import path2arr
+    from .yolodata import path2arr
     path = '/Users/apple/Desktop/8.jpg'
     threshold_index = [95.55165, 184.0512,  250.18225, 333.9927]
     image = path2arr(path)

onnx_infer/main.py

@@ -8,12 +8,12 @@ the result of this is the category and bounding box which is the max score.
 """
 #*******************
 
-from yolodata import path2Img, letterbox_image, path2arr, arr2Img
-from onnx2kera import onnxinfere
-from supression import Supress
+from .yolodata import path2Img, letterbox_image, path2arr, arr2Img
+from .onnx2kera import onnxinfere
+from .supression import Supress
 import tensorflow as tf
-from color import COLORS, featureTransform, resize, get_color
-from croppic import cropImage
+from .color import COLORS, featureTransform, resize, get_color
+from .croppic import cropImage
 import cv2
 #global
 categorys = ['long sleeve dress', 'vest dress', 'vest', 'long sleeve outwear', 'long sleeve top',

onnx_infer/onnx2kera.py

@@ -6,7 +6,7 @@ import cv2
 import numpy as np
 import keras.backend as k
 import tensorflow as tf
-from yolodata import path2Img, letterbox_image
+from .yolodata import path2Img, letterbox_image
 
 def hf2onnx(h5_path, save_path):
     model = load_model(h5_path)
@@ -23,7 +23,7 @@ def onnxinfere(onnx_path, input):
 
 
 if __name__ == '__main__':
-    from supression import Supress
+    from .supression import Supress
 #    path = '/Users/apple/Public/keras-yolo3/model_data/our1_yolo.h5'
     save_path = '/Users/apple/Desktop/yolo3.onnx'
     anncorPath = 'model_data/yolo_anchors.txt'

onnx_infer/supression.py

 import numpy as np
 from keras import backend as k
-from yolo3.model import yolo_eval
+from .yolo3.model import yolo_eval
 import os
 
 class Supress:

onnx_infer/yolo3/model.py

@@ -9,7 +9,7 @@ from keras.layers.normalization import BatchNormalization
 from keras.models import Model
 from keras.regularizers import l2
 
-from yolo3.utils import compose
+from .utils import compose
 
 
 @wraps(Conv2D)

setup.py

@@ -10,9 +10,6 @@ setup(
     url = 'http://git.wanmeizhensuo.com/wujilong/onnx_model.git',
     author_email = 'wujilong@igengmei.com',
     license = 'MIT',
-    packages = ['onnx_infer.color', onnx_infer.croppic, onnx_infer.drawpic, 'onnx_infer.main',
-                  'onnx_infer.onnx2kera',  'onnx_infer.supression', 'onnx_infer.yolodata', 
-                  'onnx_infer.yolo3.model', 'onnx_infer.yolo3.utils'],
-
+    packages = find_packages(),                                    
     )