From 23d94e4846bf4ec13069703a28b1d776f4bbe44f Mon Sep 17 00:00:00 2001
From: Edmond Yoo <hj3yoo@uwaterloo.ca>
Date: Sat, 13 Oct 2018 18:49:47 +0000
Subject: [PATCH] Cleaning & commenting #3 - refactoring constants to Config class
---
opencv_dnn.py | 14 +++++++-------
1 files changed, 7 insertions(+), 7 deletions(-)
diff --git a/opencv_dnn.py b/opencv_dnn.py
index 44503ef..9f83caa 100644
--- a/opencv_dnn.py
+++ b/opencv_dnn.py
@@ -9,8 +9,8 @@
from PIL import Image
import time
+from config import Config
import fetch_data
-import transform_data
"""
@@ -54,7 +54,7 @@
for card_name in card_names:
# Fetch the image - name can be found based on the card's information
card_info['name'] = card_name
- img_name = '%s/card_img/png/%s/%s_%s.png' % (transform_data.data_dir, card_info['set'],
+ img_name = '%s/card_img/png/%s/%s_%s.png' % (Config.data_dir, card_info['set'],
card_info['collector_number'],
fetch_data.get_valid_filename(card_info['name']))
card_img = cv2.imread(img_name)
@@ -62,7 +62,7 @@
# If the image doesn't exist, download it from the URL
if card_img is None:
fetch_data.fetch_card_image(card_info,
- out_dir='%s/card_img/png/%s' % (transform_data.data_dir, card_info['set']))
+ out_dir='%s/card_img/png/%s' % (Config.data_dir, card_info['set']))
card_img = cv2.imread(img_name)
if card_img is None:
print('WARNING: card %s is not found!' % img_name)
@@ -284,7 +284,7 @@
# Find the contour
_, cnts, hier = cv2.findContours(img_erode, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
if len(cnts) == 0:
- print('no contours')
+ #print('no contours')
return []
# The hierarchy from cv2.findContours() is similar to a tree: each node has an access to the parent, the first child
@@ -343,7 +343,7 @@
card_set = key[key.find('(') + 1:key.find(')')]
confidence = sum(val) / f_len
card_info = card_pool[(card_pool['name'] == card_name) & (card_pool['set'] == card_set)].iloc[0]
- img_name = '%s/card_img/tiny/%s/%s_%s.png' % (transform_data.data_dir, card_info['set'],
+ img_name = '%s/card_img/tiny/%s/%s_%s.png' % (Config.data_dir, card_info['set'],
card_info['collector_number'],
fetch_data.get_valid_filename(card_info['name']))
# If the card image is not found, just leave it blank
@@ -542,8 +542,8 @@
else:
# Merge database for all cards, then calculate pHash values of each, store them
df_list = []
- for set_name in fetch_data.all_set_list:
- csv_name = '%s/csv/%s.csv' % (transform_data.data_dir, set_name)
+ for set_name in Config.all_set_list:
+ csv_name = '%s/csv/%s.csv' % (Config.data_dir, set_name)
df = fetch_data.load_all_cards_text(csv_name)
df_list.append(df)
card_pool = pd.concat(df_list, sort=True)
--
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