From 2292d6ff94a17c4e158c168de23cff0f62603dc1 Mon Sep 17 00:00:00 2001
From: SpeedProg <speedprog@googlemail.com>
Date: Thu, 02 Jan 2020 15:56:20 +0000
Subject: [PATCH] update stuff
---
opencv_dnn.py | 22 +++++++++++++++++-----
1 files changed, 17 insertions(+), 5 deletions(-)
diff --git a/opencv_dnn.py b/opencv_dnn.py
index 321bcd3..4b2c4e0 100755
--- a/opencv_dnn.py
+++ b/opencv_dnn.py
@@ -89,6 +89,7 @@
#img_art = Image.fromarray(card_img[121:580, 63:685]) # For 745*1040 size card image
img_card = Image.fromarray(card_img)
img_set = Image.fromarray(set_img)
+ #cv2.imshow('Set' + card_names[0], set_img)
for hs in hash_size:
card_hash = ih.phash(img_card, hash_size=hs)
set_hash = ih.whash(img_set, hash_size=64)
@@ -262,7 +263,7 @@
# 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 []
img_cont = cv2.cvtColor(img_erode, cv2.COLOR_GRAY2BGR)
img_cont_base = img_cont.copy()
@@ -288,6 +289,8 @@
size = cv2.contourArea(cnt)
peri = cv2.arcLength(cnt, True)
approx = cv2.approxPolyDP(cnt, 0.04 * peri, True)
+ print('Base Size:', size)
+ print('Len Approx:', len(approx))
if size >= size_thresh and len(approx) == 4:
# lets see if we got a contour very close in size as child
if i_child != -1:
@@ -304,7 +307,7 @@
c_cnt = c_list[0] # the biggest child
if debug:
cv2.drawContours(img_ccont, c_list[:1], -1, (0, 255, 0), 1)
- cv2.imshow('CCont %d' % i_cnt, img_ccont)
+ cv2.imshow('CCont', img_ccont)
c_size = cv2.contourArea(c_cnt)
c_approx = cv2.approxPolyDP(c_cnt, 0.04 * peri, True)
if len(c_approx) == 4 and (c_size/size) > 0.85:
@@ -412,7 +415,9 @@
det_cards = []
# Detect contours of all cards in the image
cnts = find_card(img_result, size_thresh=size_thresh, debug=debug)
+ print('Countours:', len(cnts))
for i in range(len(cnts)):
+ print('Contour', i)
cnt = cnts[i]
# For the region of the image covered by the contour, transform them into a rectangular image
pts = np.float32([p[0] for p in cnt])
@@ -437,6 +442,7 @@
img_set_part = img_warp[cut[0]:cut[1], cut[2]:cut[3]]
print(img_set_part.shape)
img_set = Image.fromarray(img_set_part.astype('uint8'), 'RGB')
+ print('img set')
if debug:
cv2.imshow("Set Img#%d" % i, img_set_part)
@@ -485,9 +491,10 @@
cv2.imshow('card#%d' % i, img_warp)
if display:
cv2.imshow('Result', img_result)
- cv2.waitKey(0)
+ inp = cv2.waitKey(0)
if out_path is not None:
+ print(out_path)
cv2.imwrite(out_path, img_result.astype(np.uint8))
return det_cards, img_result
@@ -618,7 +625,9 @@
print('Elapsed time: %.2f ms' % elapsed_ms)
if out_path is not None:
vid_writer.write(img_save.astype(np.uint8))
- cv2.waitKey(1)
+ inp = cv2.waitKey(0)
+ if 'q' == chr(inp & 255):
+ break
except KeyboardInterrupt:
capture.release()
if out_path is not None:
@@ -677,8 +686,11 @@
capture.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc(*"MJPG"))
capture.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)
+
+ thres = int(((1920-2*500)*(1080-2*200)*0.3))
+ print('Threshold:', thres)
detect_video(capture, card_pool, hash_size=args.hash_size, out_path='%s/result.avi' % args.out_path,
- display=args.display, show_graph=args.show_graph, debug=args.debug, crop_x=500, crop_y=200)
+ display=args.display, show_graph=args.show_graph, debug=args.debug, crop_x=500, crop_y=200, size_thresh=thres)
capture.release()
else:
# Save the detection result if args.out_path is provided
--
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