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| author | Jules Laplace <julescarbon@gmail.com> | 2020-02-12 13:59:15 +0100 |
|---|---|---|
| committer | Jules Laplace <julescarbon@gmail.com> | 2020-02-12 13:59:15 +0100 |
| commit | 7a9be5eff266bc180fffa3b0e28b12a0dbcca2a3 (patch) | |
| tree | 15854640d5094cc7041a1ec334c2e703109ff9d6 /cli/app/search/search_dense.py | |
| parent | 4a4676ef9e9698bab8aa224f52b45382bc271ff0 (diff) | |
deeper pass
Diffstat (limited to 'cli/app/search/search_dense.py')
| -rw-r--r-- | cli/app/search/search_dense.py | 18 |
1 files changed, 9 insertions, 9 deletions
diff --git a/cli/app/search/search_dense.py b/cli/app/search/search_dense.py index e6c4c2a..85adc2f 100644 --- a/cli/app/search/search_dense.py +++ b/cli/app/search/search_dense.py @@ -216,15 +216,15 @@ def find_dense_embedding_for_images(params, opt_tag="inverse_" + timestamp(), op feat_loss_d, feat_err_d = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, img_w - width, img_w - width, height, width) feat_loss_e, feat_err_e = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, int((img_w - width) / 2), int((img_w - width) / 2), height, width) - feat_loss_aa, feat_err_aa = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, 0, 0, height/3, width/3, height, width) - feat_loss_ab, feat_err_ab = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, height*1/3, 0, height/3, width/3, height, width) - feat_loss_ac, feat_err_ac = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, height*2/3, 0, height/3, width/3, height, width) - feat_loss_ad, feat_err_ad = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, 0, width*1/3, height/3, width/3, height, width) - feat_loss_ae, feat_err_ae = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, height*1/3, width*1/3, height/3, width/3, height, width) - feat_loss_af, feat_err_af = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, height*2/3, width*1/3, height/3, width/3, height, width) - feat_loss_ag, feat_err_ag = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, 0, width*2/3, height/3, width/3, height, width) - feat_loss_ah, feat_err_ah = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, height*1/3, width*2/3, height/3, width/3, height, width) - feat_loss_ai, feat_err_ai = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, height*2/3, width*2/3, height/3, width/3, height, width) + feat_loss_aa, feat_err_aa = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, 0, 0, img_w/3, img_w/3, height, width) + feat_loss_ab, feat_err_ab = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, img_w*1/3, 0, img_w/3, img_w/3, height, width) + feat_loss_ac, feat_err_ac = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, img_w*2/3, 0, img_w/3, img_w/3, height, width) + feat_loss_ad, feat_err_ad = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, 0, img_w*1/3, img_w/3, img_w/3, height, width) + feat_loss_ae, feat_err_ae = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, img_w*1/3, img_w*1/3, img_w/3, img_w/3, height, width) + feat_loss_af, feat_err_af = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, img_w*2/3, img_w*1/3, img_w/3, img_w/3, height, width) + feat_loss_ag, feat_err_ag = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, 0, img_w*2/3, img_w/3, img_w/3, height, width) + feat_loss_ah, feat_err_ah = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, img_w*1/3, img_w*2/3, img_w/3, img_w/3, height, width) + feat_loss_ai, feat_err_ai = feature_loss(feature_extractor, opt_feature_layers, BATCH_SIZE, gen_img_ch, target_img_ch, img_w*2/3, img_w*2/3, img_w/3, img_w/3, height, width) mse_loss_a = mse_loss_crop(target_img_ch, gen_img_ch, 0, 0, img_w / 2, img_w / 2) mse_loss_b = mse_loss_crop(target_img_ch, gen_img_ch, img_w / 2, 0, img_w / 2, img_w / 2) |