update

qixuxiang · May 7, 2019 · 11a6c8d · 11a6c8d
1 parent 5efa4e2
commit 11a6c8d
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Showing 4 changed files with 17 additions and 20,270 deletions.
diff --git a/tools/dfsign_submit.py b/tools/dfsign_submit.py
@@ -26,7 +26,7 @@
 # chip loc
 loc_json = os.path.join(anno_dir, 'test_chip.json')
 # detections
-detect_json = os.path.join(home, 'working/dfsign/yolov3/output/results.json')
+detect_json = os.path.join(home, 'working/dfsign/faster-rcnn.pytorch/output/results.json')
 
 def main():
     # read chip loc
@@ -38,21 +38,22 @@ def main():
 
     dfsign_results = []
     for chip_id, chip_result in chip_detect.items():
+        chip_id = os.path.basename(chip_id)
         img_id = chip_id.split('_')[0] + '.jpg'
 
         loc = chip_loc[chip_id]['loc']
         for i, pred_box in enumerate(chip_result['pred_box']):
             # transform to orginal image
-            ratio = (loc[2] - loc[0]) / 416.
-            pred_box = [pred_box[0] * ratio + loc[0],
-                        pred_box[1] * ratio + loc[1],
-                        pred_box[2] * ratio + loc[0],
-                        pred_box[3] * ratio + loc[1]]
+            # ratio = (loc[2] - loc[0]) / 416.
+            pred_box = [pred_box[0] + loc[0] + 1,
+                        pred_box[1] + loc[1] + 1,
+                        pred_box[2] + loc[0] + 1,
+                        pred_box[3] + loc[1] + 1]
             sign_type = int(chip_result['pred_label'][i])
             score = chip_result['pred_score'][i]
             pred_box = [pred_box[0], pred_box[1], pred_box[2], pred_box[1],
                         pred_box[2], pred_box[3], pred_box[0], pred_box[3]]
-            pred_box = [int(x) for x in pred_box]
+            # pred_box = [int(x) for x in pred_box]
             dfsign_results.append([img_id] + pred_box + [sign_type, score])
 
     filter_results = []

diff --git a/tools/generate_mask_chip.py b/tools/generate_mask_chip.py
@@ -46,15 +46,15 @@ def mask_chip(mask_box, image_size):
         box_cy = box[1] + box_h / 2
 
         if box_w < 100 and box_h < 100:
-            chip_size = max(box_w, box_h)+150
+            chip_size = max(box_w, box_h)+50
         elif box_w < 150 and box_h < 150:
-            chip_size = max(box_w, box_h)+150
+            chip_size = max(box_w, box_h)+50
         elif box_w < 200 and box_h < 200:
             chip_size = max(box_w, box_h)+150
         elif box_w < 300 and box_h < 300:
-            chip_size = max(box_w, box_h)+50
+            chip_size = max(box_w, box_h)+200
         else:
-            chip_size = max(box_w, box_h)+50
+            chip_size = max(box_w, box_h)+200
 
         chip = [box_cx - chip_size / 2, box_cy - chip_size / 2,
                 box_cx + chip_size / 2, box_cy + chip_size / 2]
@@ -97,7 +97,7 @@ def main():
 
         for i, chip in enumerate(chip_list):
             chip_img = origin_img[chip[1]:chip[3], chip[0]:chip[2], :].copy()
-            chip_img = cv2.resize(chip_img, (416, 416), cv2.INTER_AREA)
+            # chip_img = cv2.resize(chip_img, (416, 416), cv2.INTER_AREA)
             chip_name = '%s_%d' % (imgid, i)
             cv2.imwrite(os.path.join(image_dir, '%s.jpg'%chip_name), chip_img)
             chip_name_list.append(chip_name)

diff --git a/tools/generate_train_chip.py b/tools/generate_train_chip.py
@@ -166,6 +166,7 @@ def write_chip_and_anno(image, imgid,
     chip_list, chip_gt_list, chip_label_list):
     """write chips of one image to disk and make xml annotations
     """
+    assert len(chip_gt_list) > 0
     for i, chip in enumerate(chip_list):
         img_name = '%s_%d.jpg' % (imgid, i)
         xml_name = '%s_%d.xml' % (imgid, i)
@@ -176,7 +177,9 @@ def write_chip_and_anno(image, imgid,
         chip_img = image[chip[1]:chip[3], chip[0]:chip[2], :].copy()
         chip_img = cv2.resize(chip_img, (416, 416), interpolation=cv2.INTER_LINEAR)
 
-        dom = make_xml(chip, chip_gt_list[i] / ratio, chip_label_list[i], img_name)
+        bbox = np.array(chip_gt_list[i] / ratio, dtype=np.int)
+        bbox = np.clip(bbox, 0, 416-1)
+        dom = make_xml(chip, bbox, chip_label_list[i], img_name)
 
         cv2.imwrite(os.path.join(image_dir, img_name), chip_img)
         with open(os.path.join(anno_dir, xml_name), 'w') as f: