I hate tensorflow

YunYang1994 · YunYang1994 · commit fe123deb3fc0 · 2018-12-30T21:05:06.000+08:00
diff --git a/quick_train.py b/quick_train.py
@@ -27,7 +27,6 @@
 file_pattern = "./data/train_data/quick_train_data/tfrecords/quick_train_data*.tfrecords"
 anchors = utils.get_anchors('./data/yolo_anchors.txt')
 
-is_training = tf.placeholder(dtype=tf.bool, name="phase_train")
 dataset = tf.data.TFRecordDataset(filenames = tf.gfile.Glob(file_pattern))
 dataset = dataset.map(utils.parser(anchors, num_classes).parser_example, num_parallel_calls = 10)
 dataset = dataset.repeat().shuffle(SHUFFLE_SIZE).batch(BATCH_SIZE).prefetch(BATCH_SIZE)
@@ -36,35 +35,18 @@
 images, *y_true = example
 model = yolov3.yolov3(num_classes)
 with tf.variable_scope('yolov3'):
-    y_pred = model.forward(images, is_training=is_training)
+    y_pred = model.forward(images, is_training=False)
     loss = model.compute_loss(y_pred, y_true)
     y_pred = model.predict(y_pred)
-
-
-# # train
-# optimizer = tf.train.AdamOptimizer(LR)
-# train_op = optimizer.minimize(loss[0])
-# sess.run(tf.global_variables_initializer())
-# for epoch in range(EPOCHS):
-    # run_items = sess.run([train_op, y_pred, y_true] + loss, feed_dict={is_training:True})
-    # rec, prec, mAP = utils.evaluate(run_items[1], run_items[2], num_classes)
-
-    # print("=> EPOCH: %2d\ttotal_loss:%7.4f\tloss_coord:%7.4f\tloss_sizes:%7.4f\tloss_confs:%7.4f\tloss_class:%7.4f"
-          # "\trec:%.2f\tprec:%.2f\tmAP:%.2f"
-          # %(epoch, run_items[3], run_items[4], run_items[5], run_items[6], run_items[7], rec, prec, mAP))
-
-
-
-# test
-load_ops = utils.load_weights(tf.global_variables(scope='yolov3'), weights_path)
-sess.run(load_ops)
+    load_ops = utils.load_weights(tf.global_variables(scope='yolov3'), weights_path)
+    sess.run(load_ops)
 
 for epoch in range(EPOCHS):
-    run_items = sess.run([y_pred, y_true] + loss, feed_dict={is_training:False})
+    run_items = sess.run([y_pred, y_true] + loss)
     rec, prec, mAP = utils.evaluate(run_items[0], run_items[1], num_classes, score_thresh=0.3, iou_thresh=0.5)
 
     print("=> EPOCH: %2d\ttotal_loss:%7.4f\tloss_coord:%7.4f\tloss_sizes:%7.4f\tloss_confs:%7.4f\tloss_class:%7.4f"
-          "\trec:%.2f\tprec:%.2f\tmAP:%.2f"
+          "\trec:%7.4f\tprec:%7.4f\tmAP:%7.4f"
           %(epoch, run_items[2], run_items[3], run_items[4], run_items[5], run_items[6], rec, prec, mAP))
 
 
