윤영빈

mid commit

1 -model_checkpoint_path: "E:/savedModel\\inference_model\\segment_inference_model"
2 -all_model_checkpoint_paths: "E:/savedModel\\inference_model\\segment_inference_model"
1 -{"model": "FrameLevelLogisticModel", "feature_sizes": "1024,128", "feature_names": "rgb,audio", "frame_features": true, "label_loss": "CrossEntropyLoss"}
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1 -model_checkpoint_path: "/root/volume/youtube-8m/saved_model/inference_model/segment_inference_model"
2 -all_model_checkpoint_paths: "/root/volume/youtube-8m/saved_model/inference_model/segment_inference_model"
1 -{"model": "FrameLevelLogisticModel", "feature_sizes": "1024,128", "feature_names": "rgb,audio", "frame_features": true, "label_loss": "CrossEntropyLoss"}
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...@@ -108,10 +108,13 @@ def recommend_videos(tags, segments, tag_model_path, video_model_path, video_id_ ...@@ -108,10 +108,13 @@ def recommend_videos(tags, segments, tag_model_path, video_model_path, video_id_
108 error_tags.append(tag) 108 error_tags.append(tag)
109 109
110 kernel[k] = segment_vector 110 kernel[k] = segment_vector
111 - 111 + for t in tagKernel:
112 + print(t)
112 #여기에서 유사한 벡터들을 뽑아냄 113 #여기에서 유사한 벡터들을 뽑아냄
113 #현재는 비디오id로 영상을 얻을 수 없으므로 반환값으로 비디오 아이디와 태그들, 확률 사용 114 #현재는 비디오id로 영상을 얻을 수 없으므로 반환값으로 비디오 아이디와 태그들, 확률 사용
114 video_tags = pd.read_csv('/mnt/e/khuhub/2015104192/web/backend/yt8m/esot3ria/segment_tags.csv', encoding='utf8',error_bad_lines=False) 115 video_tags = pd.read_csv('/mnt/e/khuhub/2015104192/web/backend/yt8m/esot3ria/segment_tags.csv', encoding='utf8',error_bad_lines=False)
116 + video_tags_per_id = pd.read_csv('/mnt/e/khuhub/2015104192/web/backend/yt8m/esot3ria/videoIds.csv', encoding='utf8',error_bad_lines=False)
117 + videoId_index = 0
115 videoVectorList = [] 118 videoVectorList = []
116 segmentTagList = [] 119 segmentTagList = []
117 prevVideoId = "" 120 prevVideoId = ""
...@@ -124,7 +127,18 @@ def recommend_videos(tags, segments, tag_model_path, video_model_path, video_id_ ...@@ -124,7 +127,18 @@ def recommend_videos(tags, segments, tag_model_path, video_model_path, video_id_
124 if prevVideoId == "": 127 if prevVideoId == "":
125 prevVideoId = video_id 128 prevVideoId = video_id
126 129
127 - if video_id[0:4] != prevVideoId[0:4]: 130 + if video_id[0:4] != prevVideoId[0:4]:
131 +
132 + currentComparingVideoTags = video_tags_per_id.loc[videoId_index]
133 + videoId_index += 1
134 + print(videoTagList)
135 + print(currentComparingVideoTags)
136 + if (currentComparingVideoTags['segment1'].split(':')[0] not in videoTagList and
137 + currentComparingVideoTags['segment2'].split(':')[0] not in videoTagList and
138 + currentComparingVideoTags['segment3'].split(':')[0] not in videoTagList and
139 + currentComparingVideoTags['segment4'].split(':')[0] not in videoTagList and
140 + currentComparingVideoTags['segment5'].split(':')[0] not in videoTagList):
141 + continue
128 #여기서 모다진걸로 컨볼루션 연산 142 #여기서 모다진걸로 컨볼루션 연산
129 #convmaxima, convidx = convolution(videoVectorList,kernel,prevVideoId) 143 #convmaxima, convidx = convolution(videoVectorList,kernel,prevVideoId)
130 maxima, idx = differenceMax(segmentTagList,tagKernel,tag_vectors,videoTagList) 144 maxima, idx = differenceMax(segmentTagList,tagKernel,tag_vectors,videoTagList)
...@@ -365,7 +379,7 @@ VIDEO_ID_MODEL_PATH = "/mnt/e/khuhub/2015104192/web/backend/yt8m/esot3ria/videoI ...@@ -365,7 +379,7 @@ VIDEO_ID_MODEL_PATH = "/mnt/e/khuhub/2015104192/web/backend/yt8m/esot3ria/videoI
365 379
366 TEST_TAGS_PATH = "/mnt/e/khuhub/2015104192/web/backend/yt8m/esot3ria/test_segement_tags.csv" 380 TEST_TAGS_PATH = "/mnt/e/khuhub/2015104192/web/backend/yt8m/esot3ria/test_segement_tags.csv"
367 381
368 -''' 382 +
369 test(TAG_VECTOR_MODEL_PATH, 383 test(TAG_VECTOR_MODEL_PATH,
370 VIDEO_VECTOR_MODEL_PATH, 384 VIDEO_VECTOR_MODEL_PATH,
371 VIDEO_ID_MODEL_PATH, 385 VIDEO_ID_MODEL_PATH,
...@@ -373,4 +387,4 @@ test(TAG_VECTOR_MODEL_PATH, ...@@ -373,4 +387,4 @@ test(TAG_VECTOR_MODEL_PATH,
373 VIDEO_TAGS_PATH, 387 VIDEO_TAGS_PATH,
374 TEST_TAGS_PATH, 388 TEST_TAGS_PATH,
375 5) 389 5)
376 - '''
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390 +
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