From e3f280fde2fe295477aff41c31ccedd0a4ef4e3a Mon Sep 17 00:00:00 2001
From: Edmond Yoo <hj3yoo@uwaterloo.ca>
Date: Thu, 30 Aug 2018 23:13:54 +0000
Subject: [PATCH] Visibility criteria for objects
---
transform_data.py | 40 ++++++++++++++++++++++++++++++++++------
1 files changed, 34 insertions(+), 6 deletions(-)
diff --git a/transform_data.py b/transform_data.py
index 719b11f..990896d 100644
--- a/transform_data.py
+++ b/transform_data.py
@@ -6,6 +6,7 @@
import pandas as pd
import fetch_data
import generate_data
+from shapely import geometry
card_mask = cv2.imread('data/mask.png')
@@ -50,6 +51,7 @@
Display the current state of the generator
:return: none
"""
+ self.check_visibility()
img_bg = cv2.resize(self.img_bg, (self.width, self.height))
for card in self.cards:
@@ -84,11 +86,12 @@
img_bg_crop = np.where(img_card_crop, img_card_crop, img_bg_crop)
img_bg[bg_crop_y1:bg_crop_y2, bg_crop_x1:bg_crop_x2] = img_bg_crop
- #for extracted_object in card.objects:
- # for pt in extracted_object.key_pts:
- # cv2.circle(img_bg, card.coordinate_in_generator(pt[0], pt[1]), 2, (0, 0, 255), 2)
- # bounding_box = card.bb_in_generator(extracted_object.key_pts)
- # cv2.rectangle(img_bg, bounding_box[0], bounding_box[2], (0, 255, 0), 2)
+ for ext_obj in card.objects:
+ if ext_obj.visible:
+ for pt in ext_obj.key_pts:
+ cv2.circle(img_bg, card.coordinate_in_generator(pt[0], pt[1]), 2, (0, 0, 255), 2)
+ bounding_box = card.bb_in_generator(ext_obj.key_pts)
+ cv2.rectangle(img_bg, bounding_box[0], bounding_box[2], (0, 255, 0), 2)
cv2.imshow('Result', img_bg)
cv2.waitKey(0)
@@ -115,6 +118,30 @@
"""
pass
+ def check_visibility(self, visibility=0.5):
+ """
+ Check whether if extracted objects in each card are visible in the current scenario, and update their status
+ :param visibility: minimum ratio of the object's area that aren't covered by another card to be visible
+ :return: none
+ """
+ card_poly_list = [geometry.Polygon([card.coordinate_in_generator(0, 0),
+ card.coordinate_in_generator(0, len(card.img)),
+ card.coordinate_in_generator(len(card.img[0]), len(card.img)),
+ card.coordinate_in_generator(len(card.img[0]), 0)]) for card in self.cards]
+
+ # First card in the list is overlaid on the bottom of the card pile
+ for i in range(len(self.cards)):
+ card = self.cards[i]
+ for ext_obj in card.objects:
+ obj_poly = geometry.Polygon([card.coordinate_in_generator(pt[0], pt[1]) for pt in ext_obj.key_pts])
+ obj_area = obj_poly.area
+ # Check if the other cards are blocking this object
+ for card_poly in card_poly_list[i + 1:]:
+ obj_poly = obj_poly.difference(card_poly)
+ visible_area = obj_poly.area
+ print("%s: %.1f visible" % (ext_obj.label, visible_area / obj_area))
+ ext_obj.visible = obj_area * visibility <= visible_area
+
def export_training_data(self, out_dir):
"""
Export the generated training image along with the txt file for all bounding boxes
@@ -241,6 +268,7 @@
def __init__(self, label, key_pts):
self.label = label
self.key_pts = key_pts
+ self.visible = False
def main():
@@ -256,7 +284,7 @@
if not is_planeswalker:
card_pool = card_pool.append(card_info)
a = 1
- for i in [random.randrange(0, card_pool.shape[0] - 1, 1) for _ in range(24)]:
+ for i in [random.randrange(0, card_pool.shape[0] - 1, 1) for _ in range(20)]:
card_info = card_pool.iloc[i]
img_name = '../usb/data/png/%s/%s_%s.png' % (card_info['set'], card_info['collector_number'],
fetch_data.get_valid_filename(card_info['name']))
--
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