From dd0da4006de7eb46ddafb108518733ef2f76b5d8 Mon Sep 17 00:00:00 2001
From: Fajar Ulin Nuha <fajarunuha@gmail.com>
Date: Fri, 11 May 2018 15:36:54 +0700
Subject: [PATCH 1/2] fix read issue

(cherry picked from commit 892fb79)
---
 predict.py | 13 ++++++++++++-
 1 file changed, 12 insertions(+), 1 deletion(-)

diff --git a/predict.py b/predict.py
index 544e29ea6..3d4c4d43c 100644
--- a/predict.py
+++ b/predict.py
@@ -9,6 +9,7 @@
 from utils import draw_boxes
 from frontend import YOLO
 import json
+import glob
 
 os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID"
 os.environ["CUDA_VISIBLE_DEVICES"]="0"
@@ -81,7 +82,17 @@ def _main_(args):
             video_writer.write(np.uint8(image))
 
         video_reader.release()
-        video_writer.release()  
+        video_writer.release()
+
+    elif image_path[-1] == '/':
+        for img in glob.glob(image_path+"*.jpg"):
+            image = cv2.imread(img)
+            boxes = yolo.predict(image)
+            image = draw_boxes(image, boxes, config['model']['labels'])
+
+            print(len(boxes), 'boxes are found')
+            cv2.imwrite(img[:-4] + '_detected' + img[-4:], image)
+
     else:
         image = cv2.imread(image_path)
         boxes = yolo.predict(image)

From b86d072224a7999168a3027b4f8ce5c2a282b0f0 Mon Sep 17 00:00:00 2001
From: Fajar Ulin Nuha <fajarunuha@gmail.com>
Date: Fri, 11 May 2018 16:40:45 +0700
Subject: [PATCH 2/2] Add direction in the README

(cherry picked from commit 1e2e70f)
---
 README.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/README.md b/README.md
index d06b7f498..1b301060a 100644
--- a/README.md
+++ b/README.md
@@ -136,6 +136,10 @@ By the end of this process, the code will write the weights of the best model to
 
 It carries out detection on the image and write the image with detected bounding boxes to the same folder.
 
+or you can also detect the whole images in a directory by specifying the directory path (the path should end with "/")
+
+`python predict.py -c config.json -w /path/to/best_weights.h5 -i /path/to/image/folder/`
+
 ## Usage for jupyter notebook
 
 Refer to the notebook (https://github.com/experiencor/basic-yolo-keras/blob/master/Yolo%20Step-by-Step.ipynb) for a complete walk-through implementation of YOLOv2 from scratch (training, testing, and scoring).