CV之YOLOv3:基于Tensorflow框架利用YOLOv3算法对热播新剧《庆余年》实现目标检测

简介: CV之YOLOv3:基于Tensorflow框架利用YOLOv3算法对热播新剧《庆余年》实现目标检测


目录

搭建

1、下载代码

2、安装依赖库

3、导出COCO权重解压到checkpoint文件夹内

4、测试


 

 

搭建

1、下载代码

tensorflow-yolov3

2、安装依赖库

pip install -r ./docs/requirements.txt

3、导出COCO权重解压到checkpoint文件夹内

Exporting loaded COCO weights as TF checkpoint(yolov3_coco.ckpt

python convert_weight.py

python freeze_graph.py

 

4、测试

 

1. 2019-12-25 15:05:02.766745: I
2. => yolov3/darknet-53/Conv/weights                     (3, 3, 3, 32)
3. => yolov3/darknet-53/Conv/BatchNorm/gamma             (32,)
4. => yolov3/darknet-53/Conv/BatchNorm/beta              (32,)
5. => yolov3/darknet-53/Conv/BatchNorm/moving_mean       (32,)
6. => yolov3/darknet-53/Conv/BatchNorm/moving_variance   (32,)
7. => yolov3/darknet-53/Conv_1/weights                   (3, 3, 32, 64)
8. => yolov3/darknet-53/Conv_1/BatchNorm/gamma           (64,)
9. => yolov3/darknet-53/Conv_1/BatchNorm/beta            (64,)
10. => yolov3/darknet-53/Conv_1/BatchNorm/moving_mean     (64,)
11. => yolov3/darknet-53/Conv_1/BatchNorm/moving_variance (64,)
12. => yolov3/darknet-53/Conv_2/weights                   (1, 1, 64, 32)
13. => yolov3/darknet-53/Conv_2/BatchNorm/gamma           (32,)
14. => yolov3/darknet-53/Conv_2/BatchNorm/beta            (32,)
15. => yolov3/darknet-53/Conv_2/BatchNorm/moving_mean     (32,)
16. => yolov3/darknet-53/Conv_2/BatchNorm/moving_variance (32,)
17. => yolov3/darknet-53/Conv_3/weights                   (3, 3, 32, 64)
18. => yolov3/darknet-53/Conv_3/BatchNorm/gamma           (64,)
19. => yolov3/darknet-53/Conv_3/BatchNorm/beta            (64,)
20. => yolov3/darknet-53/Conv_3/BatchNorm/moving_mean     (64,)
21. => yolov3/darknet-53/Conv_3/BatchNorm/moving_variance (64,)
22. => yolov3/darknet-53/Conv_4/weights                   (3, 3, 64, 128)
23. => yolov3/darknet-53/Conv_4/BatchNorm/gamma           (128,)
24. => yolov3/darknet-53/Conv_4/BatchNorm/beta            (128,)
25. => yolov3/darknet-53/Conv_4/BatchNorm/moving_mean     (128,)
26. => yolov3/darknet-53/Conv_4/BatchNorm/moving_variance (128,)
27. => yolov3/darknet-53/Conv_5/weights                   (1, 1, 128, 64)
28. => yolov3/darknet-53/Conv_5/BatchNorm/gamma           (64,)
29. => yolov3/darknet-53/Conv_5/BatchNorm/beta            (64,)
30. => yolov3/darknet-53/Conv_5/BatchNorm/moving_mean     (64,)
31. => yolov3/darknet-53/Conv_5/BatchNorm/moving_variance (64,)
32. => yolov3/darknet-53/Conv_6/weights                   (3, 3, 64, 128)
33. => yolov3/darknet-53/Conv_6/BatchNorm/gamma           (128,)
34. => yolov3/darknet-53/Conv_6/BatchNorm/beta            (128,)
35. => yolov3/darknet-53/Conv_6/BatchNorm/moving_mean     (128,)
36. => yolov3/darknet-53/Conv_6/BatchNorm/moving_variance (128,)
37. => yolov3/darknet-53/Conv_7/weights                   (1, 1, 128, 64)
38. => yolov3/darknet-53/Conv_7/BatchNorm/gamma           (64,)
39. => yolov3/darknet-53/Conv_7/BatchNorm/beta            (64,)
40. => yolov3/darknet-53/Conv_7/BatchNorm/moving_mean     (64,)
41. => yolov3/darknet-53/Conv_7/BatchNorm/moving_variance (64,)
42. => yolov3/darknet-53/Conv_8/weights                   (3, 3, 64, 128)
43. => yolov3/darknet-53/Conv_8/BatchNorm/gamma           (128,)
44. => yolov3/darknet-53/Conv_8/BatchNorm/beta            (128,)
45. => yolov3/darknet-53/Conv_8/BatchNorm/moving_mean     (128,)
46. => yolov3/darknet-53/Conv_8/BatchNorm/moving_variance (128,)
47. => yolov3/darknet-53/Conv_9/weights                   (3, 3, 128, 256)
48. => yolov3/darknet-53/Conv_9/BatchNorm/gamma           (256,)
49. => yolov3/darknet-53/Conv_9/BatchNorm/beta            (256,)
50. => yolov3/darknet-53/Conv_9/BatchNorm/moving_mean     (256,)
51. => yolov3/darknet-53/Conv_9/BatchNorm/moving_variance (256,)
52. => yolov3/darknet-53/Conv_10/weights                  (1, 1, 256, 128)
53. => yolov3/darknet-53/Conv_10/BatchNorm/gamma          (128,)
54. => yolov3/darknet-53/Conv_10/BatchNorm/beta           (128,)
55. => yolov3/darknet-53/Conv_10/BatchNorm/moving_mean    (128,)
56. => yolov3/darknet-53/Conv_10/BatchNorm/moving_variance (128,)
57. => yolov3/darknet-53/Conv_11/weights                  (3, 3, 128, 256)
58. => yolov3/darknet-53/Conv_11/BatchNorm/gamma          (256,)
59. => yolov3/darknet-53/Conv_11/BatchNorm/beta           (256,)
60. => yolov3/darknet-53/Conv_11/BatchNorm/moving_mean    (256,)
61. => yolov3/darknet-53/Conv_11/BatchNorm/moving_variance (256,)
62. => yolov3/darknet-53/Conv_12/weights                  (1, 1, 256, 128)
63. => yolov3/darknet-53/Conv_12/BatchNorm/gamma          (128,)
64. => yolov3/darknet-53/Conv_12/BatchNorm/beta           (128,)
65. => yolov3/darknet-53/Conv_12/BatchNorm/moving_mean    (128,)
66. => yolov3/darknet-53/Conv_12/BatchNorm/moving_variance (128,)
67. => yolov3/darknet-53/Conv_13/weights                  (3, 3, 128, 256)
68. => yolov3/darknet-53/Conv_13/BatchNorm/gamma          (256,)
69. => yolov3/darknet-53/Conv_13/BatchNorm/beta           (256,)
70. => yolov3/darknet-53/Conv_13/BatchNorm/moving_mean    (256,)
71. => yolov3/darknet-53/Conv_13/BatchNorm/moving_variance (256,)
72. => yolov3/darknet-53/Conv_14/weights                  (1, 1, 256, 128)
73. => yolov3/darknet-53/Conv_14/BatchNorm/gamma          (128,)
74. => yolov3/darknet-53/Conv_14/BatchNorm/beta           (128,)
75. => yolov3/darknet-53/Conv_14/BatchNorm/moving_mean    (128,)
76. => yolov3/darknet-53/Conv_14/BatchNorm/moving_variance (128,)
77. => yolov3/darknet-53/Conv_15/weights                  (3, 3, 128, 256)
78. => yolov3/darknet-53/Conv_15/BatchNorm/gamma          (256,)
79. => yolov3/darknet-53/Conv_15/BatchNorm/beta           (256,)
80. => yolov3/darknet-53/Conv_15/BatchNorm/moving_mean    (256,)
81. => yolov3/darknet-53/Conv_15/BatchNorm/moving_variance (256,)
82. => yolov3/darknet-53/Conv_16/weights                  (1, 1, 256, 128)
83. => yolov3/darknet-53/Conv_16/BatchNorm/gamma          (128,)
84. => yolov3/darknet-53/Conv_16/BatchNorm/beta           (128,)
85. => yolov3/darknet-53/Conv_16/BatchNorm/moving_mean    (128,)
86. => yolov3/darknet-53/Conv_16/BatchNorm/moving_variance (128,)
87. => yolov3/darknet-53/Conv_17/weights                  (3, 3, 128, 256)
88. => yolov3/darknet-53/Conv_17/BatchNorm/gamma          (256,)
89. => yolov3/darknet-53/Conv_17/BatchNorm/beta           (256,)
90. => yolov3/darknet-53/Conv_17/BatchNorm/moving_mean    (256,)
91. => yolov3/darknet-53/Conv_17/BatchNorm/moving_variance (256,)
92. => yolov3/darknet-53/Conv_18/weights                  (1, 1, 256, 128)
93. => yolov3/darknet-53/Conv_18/BatchNorm/gamma          (128,)
94. => yolov3/darknet-53/Conv_18/BatchNorm/beta           (128,)
95. => yolov3/darknet-53/Conv_18/BatchNorm/moving_mean    (128,)
96. => yolov3/darknet-53/Conv_18/BatchNorm/moving_variance (128,)
97. => yolov3/darknet-53/Conv_19/weights                  (3, 3, 128, 256)
98. => yolov3/darknet-53/Conv_19/BatchNorm/gamma          (256,)
99. => yolov3/darknet-53/Conv_19/BatchNorm/beta           (256,)
100. => yolov3/darknet-53/Conv_19/BatchNorm/moving_mean    (256,)
101. => yolov3/darknet-53/Conv_19/BatchNorm/moving_variance (256,)
102. => yolov3/darknet-53/Conv_20/weights                  (1, 1, 256, 128)
103. => yolov3/darknet-53/Conv_20/BatchNorm/gamma          (128,)
104. => yolov3/darknet-53/Conv_20/BatchNorm/beta           (128,)
105. => yolov3/darknet-53/Conv_20/BatchNorm/moving_mean    (128,)
106. => yolov3/darknet-53/Conv_20/BatchNorm/moving_variance (128,)
107. => yolov3/darknet-53/Conv_21/weights                  (3, 3, 128, 256)
108. => yolov3/darknet-53/Conv_21/BatchNorm/gamma          (256,)
109. => yolov3/darknet-53/Conv_21/BatchNorm/beta           (256,)
110. => yolov3/darknet-53/Conv_21/BatchNorm/moving_mean    (256,)
111. => yolov3/darknet-53/Conv_21/BatchNorm/moving_variance (256,)
112. => yolov3/darknet-53/Conv_22/weights                  (1, 1, 256, 128)
113. => yolov3/darknet-53/Conv_22/BatchNorm/gamma          (128,)
114. => yolov3/darknet-53/Conv_22/BatchNorm/beta           (128,)
115. => yolov3/darknet-53/Conv_22/BatchNorm/moving_mean    (128,)
116. => yolov3/darknet-53/Conv_22/BatchNorm/moving_variance (128,)
117. => yolov3/darknet-53/Conv_23/weights                  (3, 3, 128, 256)
118. => yolov3/darknet-53/Conv_23/BatchNorm/gamma          (256,)
119. => yolov3/darknet-53/Conv_23/BatchNorm/beta           (256,)
120. => yolov3/darknet-53/Conv_23/BatchNorm/moving_mean    (256,)
121. => yolov3/darknet-53/Conv_23/BatchNorm/moving_variance (256,)
122. => yolov3/darknet-53/Conv_24/weights                  (1, 1, 256, 128)
123. => yolov3/darknet-53/Conv_24/BatchNorm/gamma          (128,)
124. => yolov3/darknet-53/Conv_24/BatchNorm/beta           (128,)
125. => yolov3/darknet-53/Conv_24/BatchNorm/moving_mean    (128,)
126. => yolov3/darknet-53/Conv_24/BatchNorm/moving_variance (128,)
127. => yolov3/darknet-53/Conv_25/weights                  (3, 3, 128, 256)
128. => yolov3/darknet-53/Conv_25/BatchNorm/gamma          (256,)
129. => yolov3/darknet-53/Conv_25/BatchNorm/beta           (256,)
130. => yolov3/darknet-53/Conv_25/BatchNorm/moving_mean    (256,)
131. => yolov3/darknet-53/Conv_25/BatchNorm/moving_variance (256,)
132. => yolov3/darknet-53/Conv_26/weights                  (3, 3, 256, 512)
133. => yolov3/darknet-53/Conv_26/BatchNorm/gamma          (512,)
134. => yolov3/darknet-53/Conv_26/BatchNorm/beta           (512,)
135. => yolov3/darknet-53/Conv_26/BatchNorm/moving_mean    (512,)
136. => yolov3/darknet-53/Conv_26/BatchNorm/moving_variance (512,)
137. => yolov3/darknet-53/Conv_27/weights                  (1, 1, 512, 256)
138. => yolov3/darknet-53/Conv_27/BatchNorm/gamma          (256,)
139. => yolov3/darknet-53/Conv_27/BatchNorm/beta           (256,)
140. => yolov3/darknet-53/Conv_27/BatchNorm/moving_mean    (256,)
141. => yolov3/darknet-53/Conv_27/BatchNorm/moving_variance (256,)
142. => yolov3/darknet-53/Conv_28/weights                  (3, 3, 256, 512)
143. => yolov3/darknet-53/Conv_28/BatchNorm/gamma          (512,)
144. => yolov3/darknet-53/Conv_28/BatchNorm/beta           (512,)
145. => yolov3/darknet-53/Conv_28/BatchNorm/moving_mean    (512,)
146. => yolov3/darknet-53/Conv_28/BatchNorm/moving_variance (512,)
147. => yolov3/darknet-53/Conv_29/weights                  (1, 1, 512, 256)
148. => yolov3/darknet-53/Conv_29/BatchNorm/gamma          (256,)
149. => yolov3/darknet-53/Conv_29/BatchNorm/beta           (256,)
150. => yolov3/darknet-53/Conv_29/BatchNorm/moving_mean    (256,)
151. => yolov3/darknet-53/Conv_29/BatchNorm/moving_variance (256,)
152. => yolov3/darknet-53/Conv_30/weights                  (3, 3, 256, 512)
153. => yolov3/darknet-53/Conv_30/BatchNorm/gamma          (512,)
154. => yolov3/darknet-53/Conv_30/BatchNorm/beta           (512,)
155. => yolov3/darknet-53/Conv_30/BatchNorm/moving_mean    (512,)
156. => yolov3/darknet-53/Conv_30/BatchNorm/moving_variance (512,)
157. => yolov3/darknet-53/Conv_31/weights                  (1, 1, 512, 256)
158. => yolov3/darknet-53/Conv_31/BatchNorm/gamma          (256,)
159. => yolov3/darknet-53/Conv_31/BatchNorm/beta           (256,)
160. => yolov3/darknet-53/Conv_31/BatchNorm/moving_mean    (256,)
161. => yolov3/darknet-53/Conv_31/BatchNorm/moving_variance (256,)
162. => yolov3/darknet-53/Conv_32/weights                  (3, 3, 256, 512)
163. => yolov3/darknet-53/Conv_32/BatchNorm/gamma          (512,)
164. => yolov3/darknet-53/Conv_32/BatchNorm/beta           (512,)
165. => yolov3/darknet-53/Conv_32/BatchNorm/moving_mean    (512,)
166. => yolov3/darknet-53/Conv_32/BatchNorm/moving_variance (512,)
167. => yolov3/darknet-53/Conv_33/weights                  (1, 1, 512, 256)
168. => yolov3/darknet-53/Conv_33/BatchNorm/gamma          (256,)
169. => yolov3/darknet-53/Conv_33/BatchNorm/beta           (256,)
170. => yolov3/darknet-53/Conv_33/BatchNorm/moving_mean    (256,)
171. => yolov3/darknet-53/Conv_33/BatchNorm/moving_variance (256,)
172. => yolov3/darknet-53/Conv_34/weights                  (3, 3, 256, 512)
173. => yolov3/darknet-53/Conv_34/BatchNorm/gamma          (512,)
174. => yolov3/darknet-53/Conv_34/BatchNorm/beta           (512,)
175. => yolov3/darknet-53/Conv_34/BatchNorm/moving_mean    (512,)
176. => yolov3/darknet-53/Conv_34/BatchNorm/moving_variance (512,)
177. => yolov3/darknet-53/Conv_35/weights                  (1, 1, 512, 256)
178. => yolov3/darknet-53/Conv_35/BatchNorm/gamma          (256,)
179. => yolov3/darknet-53/Conv_35/BatchNorm/beta           (256,)
180. => yolov3/darknet-53/Conv_35/BatchNorm/moving_mean    (256,)
181. => yolov3/darknet-53/Conv_35/BatchNorm/moving_variance (256,)
182. => yolov3/darknet-53/Conv_36/weights                  (3, 3, 256, 512)
183. => yolov3/darknet-53/Conv_36/BatchNorm/gamma          (512,)
184. => yolov3/darknet-53/Conv_36/BatchNorm/beta           (512,)
185. => yolov3/darknet-53/Conv_36/BatchNorm/moving_mean    (512,)
186. => yolov3/darknet-53/Conv_36/BatchNorm/moving_variance (512,)
187. => yolov3/darknet-53/Conv_37/weights                  (1, 1, 512, 256)
188. => yolov3/darknet-53/Conv_37/BatchNorm/gamma          (256,)
189. => yolov3/darknet-53/Conv_37/BatchNorm/beta           (256,)
190. => yolov3/darknet-53/Conv_37/BatchNorm/moving_mean    (256,)
191. => yolov3/darknet-53/Conv_37/BatchNorm/moving_variance (256,)
192. => yolov3/darknet-53/Conv_38/weights                  (3, 3, 256, 512)
193. => yolov3/darknet-53/Conv_38/BatchNorm/gamma          (512,)
194. => yolov3/darknet-53/Conv_38/BatchNorm/beta           (512,)
195. => yolov3/darknet-53/Conv_38/BatchNorm/moving_mean    (512,)
196. => yolov3/darknet-53/Conv_38/BatchNorm/moving_variance (512,)
197. => yolov3/darknet-53/Conv_39/weights                  (1, 1, 512, 256)
198. => yolov3/darknet-53/Conv_39/BatchNorm/gamma          (256,)
199. => yolov3/darknet-53/Conv_39/BatchNorm/beta           (256,)
200. => yolov3/darknet-53/Conv_39/BatchNorm/moving_mean    (256,)
201. => yolov3/darknet-53/Conv_39/BatchNorm/moving_variance (256,)
202. => yolov3/darknet-53/Conv_40/weights                  (3, 3, 256, 512)
203. => yolov3/darknet-53/Conv_40/BatchNorm/gamma          (512,)
204. => yolov3/darknet-53/Conv_40/BatchNorm/beta           (512,)
205. => yolov3/darknet-53/Conv_40/BatchNorm/moving_mean    (512,)
206. => yolov3/darknet-53/Conv_40/BatchNorm/moving_variance (512,)
207. => yolov3/darknet-53/Conv_41/weights                  (1, 1, 512, 256)
208. => yolov3/darknet-53/Conv_41/BatchNorm/gamma          (256,)
209. => yolov3/darknet-53/Conv_41/BatchNorm/beta           (256,)
210. => yolov3/darknet-53/Conv_41/BatchNorm/moving_mean    (256,)
211. => yolov3/darknet-53/Conv_41/BatchNorm/moving_variance (256,)
212. => yolov3/darknet-53/Conv_42/weights                  (3, 3, 256, 512)
213. => yolov3/darknet-53/Conv_42/BatchNorm/gamma          (512,)
214. => yolov3/darknet-53/Conv_42/BatchNorm/beta           (512,)
215. => yolov3/darknet-53/Conv_42/BatchNorm/moving_mean    (512,)
216. => yolov3/darknet-53/Conv_42/BatchNorm/moving_variance (512,)
217. => yolov3/darknet-53/Conv_43/weights                  (3, 3, 512, 1024)
218. => yolov3/darknet-53/Conv_43/BatchNorm/gamma          (1024,)
219. => yolov3/darknet-53/Conv_43/BatchNorm/beta           (1024,)
220. => yolov3/darknet-53/Conv_43/BatchNorm/moving_mean    (1024,)
221. => yolov3/darknet-53/Conv_43/BatchNorm/moving_variance (1024,)
222. => yolov3/darknet-53/Conv_44/weights                  (1, 1, 1024, 512)
223. => yolov3/darknet-53/Conv_44/BatchNorm/gamma          (512,)
224. => yolov3/darknet-53/Conv_44/BatchNorm/beta           (512,)
225. => yolov3/darknet-53/Conv_44/BatchNorm/moving_mean    (512,)
226. => yolov3/darknet-53/Conv_44/BatchNorm/moving_variance (512,)
227. => yolov3/darknet-53/Conv_45/weights                  (3, 3, 512, 1024)
228. => yolov3/darknet-53/Conv_45/BatchNorm/gamma          (1024,)
229. => yolov3/darknet-53/Conv_45/BatchNorm/beta           (1024,)
230. => yolov3/darknet-53/Conv_45/BatchNorm/moving_mean    (1024,)
231. => yolov3/darknet-53/Conv_45/BatchNorm/moving_variance (1024,)
232. => yolov3/darknet-53/Conv_46/weights                  (1, 1, 1024, 512)
233. => yolov3/darknet-53/Conv_46/BatchNorm/gamma          (512,)
234. => yolov3/darknet-53/Conv_46/BatchNorm/beta           (512,)
235. => yolov3/darknet-53/Conv_46/BatchNorm/moving_mean    (512,)
236. => yolov3/darknet-53/Conv_46/BatchNorm/moving_variance (512,)
237. => yolov3/darknet-53/Conv_47/weights                  (3, 3, 512, 1024)
238. => yolov3/darknet-53/Conv_47/BatchNorm/gamma          (1024,)
239. => yolov3/darknet-53/Conv_47/BatchNorm/beta           (1024,)
240. => yolov3/darknet-53/Conv_47/BatchNorm/moving_mean    (1024,)
241. => yolov3/darknet-53/Conv_47/BatchNorm/moving_variance (1024,)
242. => yolov3/darknet-53/Conv_48/weights                  (1, 1, 1024, 512)
243. => yolov3/darknet-53/Conv_48/BatchNorm/gamma          (512,)
244. => yolov3/darknet-53/Conv_48/BatchNorm/beta           (512,)
245. => yolov3/darknet-53/Conv_48/BatchNorm/moving_mean    (512,)
246. => yolov3/darknet-53/Conv_48/BatchNorm/moving_variance (512,)
247. => yolov3/darknet-53/Conv_49/weights                  (3, 3, 512, 1024)
248. => yolov3/darknet-53/Conv_49/BatchNorm/gamma          (1024,)
249. => yolov3/darknet-53/Conv_49/BatchNorm/beta           (1024,)
250. => yolov3/darknet-53/Conv_49/BatchNorm/moving_mean    (1024,)
251. => yolov3/darknet-53/Conv_49/BatchNorm/moving_variance (1024,)
252. => yolov3/darknet-53/Conv_50/weights                  (1, 1, 1024, 512)
253. => yolov3/darknet-53/Conv_50/BatchNorm/gamma          (512,)
254. => yolov3/darknet-53/Conv_50/BatchNorm/beta           (512,)
255. => yolov3/darknet-53/Conv_50/BatchNorm/moving_mean    (512,)
256. => yolov3/darknet-53/Conv_50/BatchNorm/moving_variance (512,)
257. => yolov3/darknet-53/Conv_51/weights                  (3, 3, 512, 1024)
258. => yolov3/darknet-53/Conv_51/BatchNorm/gamma          (1024,)
259. => yolov3/darknet-53/Conv_51/BatchNorm/beta           (1024,)
260. => yolov3/darknet-53/Conv_51/BatchNorm/moving_mean    (1024,)
261. => yolov3/darknet-53/Conv_51/BatchNorm/moving_variance (1024,)
262. => yolov3/yolo-v3/Conv/weights                        (1, 1, 1024, 512)
263. => yolov3/yolo-v3/Conv/BatchNorm/gamma                (512,)
264. => yolov3/yolo-v3/Conv/BatchNorm/beta                 (512,)
265. => yolov3/yolo-v3/Conv/BatchNorm/moving_mean          (512,)
266. => yolov3/yolo-v3/Conv/BatchNorm/moving_variance      (512,)
267. => yolov3/yolo-v3/Conv_1/weights                      (3, 3, 512, 1024)
268. => yolov3/yolo-v3/Conv_1/BatchNorm/gamma              (1024,)
269. => yolov3/yolo-v3/Conv_1/BatchNorm/beta               (1024,)
270. => yolov3/yolo-v3/Conv_1/BatchNorm/moving_mean        (1024,)
271. => yolov3/yolo-v3/Conv_1/BatchNorm/moving_variance    (1024,)
272. => yolov3/yolo-v3/Conv_2/weights                      (1, 1, 1024, 512)
273. => yolov3/yolo-v3/Conv_2/BatchNorm/gamma              (512,)
274. => yolov3/yolo-v3/Conv_2/BatchNorm/beta               (512,)
275. => yolov3/yolo-v3/Conv_2/BatchNorm/moving_mean        (512,)
276. => yolov3/yolo-v3/Conv_2/BatchNorm/moving_variance    (512,)
277. => yolov3/yolo-v3/Conv_3/weights                      (3, 3, 512, 1024)
278. => yolov3/yolo-v3/Conv_3/BatchNorm/gamma              (1024,)
279. => yolov3/yolo-v3/Conv_3/BatchNorm/beta               (1024,)
280. => yolov3/yolo-v3/Conv_3/BatchNorm/moving_mean        (1024,)
281. => yolov3/yolo-v3/Conv_3/BatchNorm/moving_variance    (1024,)
282. => yolov3/yolo-v3/Conv_4/weights                      (1, 1, 1024, 512)
283. => yolov3/yolo-v3/Conv_4/BatchNorm/gamma              (512,)
284. => yolov3/yolo-v3/Conv_4/BatchNorm/beta               (512,)
285. => yolov3/yolo-v3/Conv_4/BatchNorm/moving_mean        (512,)
286. => yolov3/yolo-v3/Conv_4/BatchNorm/moving_variance    (512,)
287. => yolov3/yolo-v3/Conv_5/weights                      (3, 3, 512, 1024)
288. => yolov3/yolo-v3/Conv_5/BatchNorm/gamma              (1024,)
289. => yolov3/yolo-v3/Conv_5/BatchNorm/beta               (1024,)
290. => yolov3/yolo-v3/Conv_5/BatchNorm/moving_mean        (1024,)
291. => yolov3/yolo-v3/Conv_5/BatchNorm/moving_variance    (1024,)
292. => yolov3/yolo-v3/Conv_6/weights                      (1, 1, 1024, 255)
293. => yolov3/yolo-v3/Conv_6/biases                       (255,)
294. => yolov3/yolo-v3/Conv_7/weights                      (1, 1, 512, 256)
295. => yolov3/yolo-v3/Conv_7/BatchNorm/gamma              (256,)
296. => yolov3/yolo-v3/Conv_7/BatchNorm/beta               (256,)
297. => yolov3/yolo-v3/Conv_7/BatchNorm/moving_mean        (256,)
298. => yolov3/yolo-v3/Conv_7/BatchNorm/moving_variance    (256,)
299. => yolov3/yolo-v3/Conv_8/weights                      (1, 1, 768, 256)
300. => yolov3/yolo-v3/Conv_8/BatchNorm/gamma              (256,)
301. => yolov3/yolo-v3/Conv_8/BatchNorm/beta               (256,)
302. => yolov3/yolo-v3/Conv_8/BatchNorm/moving_mean        (256,)
303. => yolov3/yolo-v3/Conv_8/BatchNorm/moving_variance    (256,)
304. => yolov3/yolo-v3/Conv_9/weights                      (3, 3, 256, 512)
305. => yolov3/yolo-v3/Conv_9/BatchNorm/gamma              (512,)
306. => yolov3/yolo-v3/Conv_9/BatchNorm/beta               (512,)
307. => yolov3/yolo-v3/Conv_9/BatchNorm/moving_mean        (512,)
308. => yolov3/yolo-v3/Conv_9/BatchNorm/moving_variance    (512,)
309. => yolov3/yolo-v3/Conv_10/weights                     (1, 1, 512, 256)
310. => yolov3/yolo-v3/Conv_10/BatchNorm/gamma             (256,)
311. => yolov3/yolo-v3/Conv_10/BatchNorm/beta              (256,)
312. => yolov3/yolo-v3/Conv_10/BatchNorm/moving_mean       (256,)
313. => yolov3/yolo-v3/Conv_10/BatchNorm/moving_variance   (256,)
314. => yolov3/yolo-v3/Conv_11/weights                     (3, 3, 256, 512)
315. => yolov3/yolo-v3/Conv_11/BatchNorm/gamma             (512,)
316. => yolov3/yolo-v3/Conv_11/BatchNorm/beta              (512,)
317. => yolov3/yolo-v3/Conv_11/BatchNorm/moving_mean       (512,)
318. => yolov3/yolo-v3/Conv_11/BatchNorm/moving_variance   (512,)
319. => yolov3/yolo-v3/Conv_12/weights                     (1, 1, 512, 256)
320. => yolov3/yolo-v3/Conv_12/BatchNorm/gamma             (256,)
321. => yolov3/yolo-v3/Conv_12/BatchNorm/beta              (256,)
322. => yolov3/yolo-v3/Conv_12/BatchNorm/moving_mean       (256,)
323. => yolov3/yolo-v3/Conv_12/BatchNorm/moving_variance   (256,)
324. => yolov3/yolo-v3/Conv_13/weights                     (3, 3, 256, 512)
325. => yolov3/yolo-v3/Conv_13/BatchNorm/gamma             (512,)
326. => yolov3/yolo-v3/Conv_13/BatchNorm/beta              (512,)
327. => yolov3/yolo-v3/Conv_13/BatchNorm/moving_mean       (512,)
328. => yolov3/yolo-v3/Conv_13/BatchNorm/moving_variance   (512,)
329. => yolov3/yolo-v3/Conv_14/weights                     (1, 1, 512, 255)
330. => yolov3/yolo-v3/Conv_14/biases                      (255,)
331. => yolov3/yolo-v3/Conv_15/weights                     (1, 1, 256, 128)
332. => yolov3/yolo-v3/Conv_15/BatchNorm/gamma             (128,)
333. => yolov3/yolo-v3/Conv_15/BatchNorm/beta              (128,)
334. => yolov3/yolo-v3/Conv_15/BatchNorm/moving_mean       (128,)
335. => yolov3/yolo-v3/Conv_15/BatchNorm/moving_variance   (128,)
336. => yolov3/yolo-v3/Conv_16/weights                     (1, 1, 384, 128)
337. => yolov3/yolo-v3/Conv_16/BatchNorm/gamma             (128,)
338. => yolov3/yolo-v3/Conv_16/BatchNorm/beta              (128,)
339. => yolov3/yolo-v3/Conv_16/BatchNorm/moving_mean       (128,)
340. => yolov3/yolo-v3/Conv_16/BatchNorm/moving_variance   (128,)
341. => yolov3/yolo-v3/Conv_17/weights                     (3, 3, 128, 256)
342. => yolov3/yolo-v3/Conv_17/BatchNorm/gamma             (256,)
343. => yolov3/yolo-v3/Conv_17/BatchNorm/beta              (256,)
344. => yolov3/yolo-v3/Conv_17/BatchNorm/moving_mean       (256,)
345. => yolov3/yolo-v3/Conv_17/BatchNorm/moving_variance   (256,)
346. => yolov3/yolo-v3/Conv_18/weights                     (1, 1, 256, 128)
347. => yolov3/yolo-v3/Conv_18/BatchNorm/gamma             (128,)
348. => yolov3/yolo-v3/Conv_18/BatchNorm/beta              (128,)
349. => yolov3/yolo-v3/Conv_18/BatchNorm/moving_mean       (128,)
350. => yolov3/yolo-v3/Conv_18/BatchNorm/moving_variance   (128,)
351. => yolov3/yolo-v3/Conv_19/weights                     (3, 3, 128, 256)
352. => yolov3/yolo-v3/Conv_19/BatchNorm/gamma             (256,)
353. => yolov3/yolo-v3/Conv_19/BatchNorm/beta              (256,)
354. => yolov3/yolo-v3/Conv_19/BatchNorm/moving_mean       (256,)
355. => yolov3/yolo-v3/Conv_19/BatchNorm/moving_variance   (256,)
356. => yolov3/yolo-v3/Conv_20/weights                     (1, 1, 256, 128)
357. => yolov3/yolo-v3/Conv_20/BatchNorm/gamma             (128,)
358. => yolov3/yolo-v3/Conv_20/BatchNorm/beta              (128,)
359. => yolov3/yolo-v3/Conv_20/BatchNorm/moving_mean       (128,)
360. => yolov3/yolo-v3/Conv_20/BatchNorm/moving_variance   (128,)
361. => yolov3/yolo-v3/Conv_21/weights                     (3, 3, 128, 256)
362. => yolov3/yolo-v3/Conv_21/BatchNorm/gamma             (256,)
363. => yolov3/yolo-v3/Conv_21/BatchNorm/beta              (256,)
364. => yolov3/yolo-v3/Conv_21/BatchNorm/moving_mean       (256,)
365. => yolov3/yolo-v3/Conv_21/BatchNorm/moving_variance   (256,)
366. => yolov3/yolo-v3/Conv_22/weights                     (1, 1, 256, 255)
367. => yolov3/yolo-v3/Conv_22/biases                      (255,)
368.

 

Tensor("conv_sbbox/BiasAdd:0", shape=(?, ?, ?, 255), dtype=float32) Tensor("conv_mbbox/BiasAdd:0", shape=(?, ?, ?, 255), dtype=float32) Tensor("conv_lbbox/BiasAdd:0", shape=(?, ?, ?, 255), dtype=float32)

 

 

相关文章
|
3天前
|
机器学习/深度学习 算法 TensorFlow
文本分类识别Python+卷积神经网络算法+TensorFlow模型训练+Django可视化界面
文本分类识别Python+卷积神经网络算法+TensorFlow模型训练+Django可视化界面
72 0
文本分类识别Python+卷积神经网络算法+TensorFlow模型训练+Django可视化界面
|
3天前
|
机器学习/深度学习 TensorFlow 算法框架/工具
关于Tensorflow!目标检测预训练模型的迁移学习
这篇文章主要介绍了使用Tensorflow进行目标检测的迁移学习过程。关于使用Tensorflow进行目标检测模型训练的实战教程,涵盖了从数据准备到模型应用的全过程,特别适合对此领域感兴趣的开发者参考。
17 3
关于Tensorflow!目标检测预训练模型的迁移学习
|
3天前
|
机器学习/深度学习 数据可视化 PyTorch
TensorFlow与PyTorch框架的深入对比:特性、优势与应用场景
【5月更文挑战第4天】本文对比了深度学习主流框架TensorFlow和PyTorch的特性、优势及应用场景。TensorFlow以其静态计算图、高性能及TensorBoard可视化工具适合大规模数据处理和复杂模型,但学习曲线较陡峭。PyTorch则以动态计算图、易用性和灵活性见长,便于研究和原型开发,但在性能和部署上有局限。选择框架应根据具体需求和场景。
|
6月前
|
算法 测试技术 计算机视觉
2023年秋招算法面经:Tp-link cv图像算法面经
2023年秋招算法面经:Tp-link cv图像算法面经
42 0
|
3天前
|
人工智能 TensorFlow 算法框架/工具
|
3天前
|
机器学习/深度学习 人工智能 算法
鱼类识别Python+深度学习人工智能+TensorFlow+卷积神经网络算法
鱼类识别Python+深度学习人工智能+TensorFlow+卷积神经网络算法
52 2
鱼类识别Python+深度学习人工智能+TensorFlow+卷积神经网络算法
|
3天前
|
机器学习/深度学习 TensorFlow 算法框架/工具
【深度学习】Tensorflow、MindSpore框架介绍及张量算子操作实战(超详细 附源码)
【深度学习】Tensorflow、MindSpore框架介绍及张量算子操作实战(超详细 附源码)
71 0
|
3天前
|
机器学习/深度学习 算法 TensorFlow
【Keras+计算机视觉+Tensorflow】实现基于YOLO和Deep Sort的目标检测与跟踪实战(附源码和数据集)
【Keras+计算机视觉+Tensorflow】实现基于YOLO和Deep Sort的目标检测与跟踪实战(附源码和数据集)
53 1
|
3天前
|
机器学习/深度学习 算法 TensorFlow
【计算机视觉+Tensorflow】SORT目标跟踪算法的讲解(图文解释 超详细)
【计算机视觉+Tensorflow】SORT目标跟踪算法的讲解(图文解释 超详细)
94 0
|
3天前
|
机器学习/深度学习 TensorFlow API
【Python/人工智能】TensorFlow 框架基本原理及使用
【Python/人工智能】TensorFlow 框架基本原理及使用
86 0