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eynollah
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updating textregions dilation

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pull/138/head^2
vahidrezanezhad 3 months ago
parent b33739adee
commit 95effe54a0
1 changed files with 139 additions and 12 deletions
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qurator/eynollah/eynollah.py
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@ -2054,7 +2054,7 @@ class Eynollah:
mask_texts_only = mask_texts_only.astype('uint8')
mask_texts_only = cv2.erode(mask_texts_only, KERNEL, iterations=1)
#mask_texts_only = cv2.erode(mask_texts_only, KERNEL, iterations=1)
mask_texts_only = cv2.dilate(mask_texts_only, KERNEL, iterations=1)
mask_images_only=(prediction_regions_org[:,:] ==2)*1
@ -3846,18 +3846,22 @@ class Eynollah:
return x_differential_new
def dilate_textregions_contours(self,all_found_textline_polygons):
#print(all_found_textline_polygons)
for j in range(len(all_found_textline_polygons)):
con_ind = all_found_textline_polygons[j]
area = cv2.contourArea(con_ind)
con_ind = con_ind.astype(np.float)
con_ind[:,0,0] = gaussian_filter1d(con_ind[:,0,0], 0.1)
con_ind[:,0,1] = gaussian_filter1d(con_ind[:,0,1], 0.1)
x_differential = np.diff( con_ind[:,0,0])
y_differential = np.diff( con_ind[:,0,1])
x_differential = gaussian_filter1d(x_differential, 3)
y_differential = gaussian_filter1d(y_differential, 3)
x_differential = gaussian_filter1d(x_differential, .5)
y_differential = gaussian_filter1d(y_differential, .5)
x_min = float(np.min( con_ind[:,0,0] ))
y_min = float(np.min( con_ind[:,0,1] ))
@ -3873,23 +3877,54 @@ class Eynollah:
inc_x = np.zeros(len(x_differential)+1)
inc_y = np.zeros(len(x_differential)+1)
if (y_max-y_min) <= (x_max-x_min):
dilation_m1 = round(area / (x_max-x_min) * 0.12)
else:
dilation_m1 = round(area / (y_max-y_min) * 0.12)
if dilation_m1>8:
dilation_m1 = 8
if dilation_m1<5:
dilation_m1 = 5
#print(dilation_m1, 'dilation_m1')
dilation_m2 = int(dilation_m1/2.) +1
for i in range(len(x_differential)):
if abs_diff[i]==0:
inc_x[i+1] = 7*(-1*y_differential_mask_nonzeros[i])
inc_y[i+1] = 7*(x_differential_mask_nonzeros[i])
inc_x[i+1] = dilation_m2*(-1*y_differential_mask_nonzeros[i])
inc_y[i+1] = dilation_m2*(x_differential_mask_nonzeros[i])
elif abs_diff[i]!=0 and x_differential_mask_nonzeros[i]==0 and y_differential_mask_nonzeros[i]!=0:
inc_x[i+1]= 12*(-1*y_differential_mask_nonzeros[i])
inc_x[i+1]= dilation_m1*(-1*y_differential_mask_nonzeros[i])
elif abs_diff[i]!=0 and x_differential_mask_nonzeros[i]!=0 and y_differential_mask_nonzeros[i]==0:
inc_y[i+1] = 12*(x_differential_mask_nonzeros[i])
inc_y[i+1] = dilation_m1*(x_differential_mask_nonzeros[i])
elif abs_diff[i]!=0 and abs_diff[i]>=3:
if abs(x_differential[i])>abs(y_differential[i]):
inc_y[i+1] = 12*(x_differential_mask_nonzeros[i])
inc_y[i+1] = dilation_m1*(x_differential_mask_nonzeros[i])
else:
inc_x[i+1]= 12*(-1*y_differential_mask_nonzeros[i])
inc_x[i+1]= dilation_m1*(-1*y_differential_mask_nonzeros[i])
else:
inc_x[i+1] = 7*(-1*y_differential_mask_nonzeros[i])
inc_y[i+1] = 7*(x_differential_mask_nonzeros[i])
inc_x[i+1] = dilation_m2*(-1*y_differential_mask_nonzeros[i])
inc_y[i+1] = dilation_m2*(x_differential_mask_nonzeros[i])
###for i in range(len(x_differential)):
###if abs_diff[i]==0:
###inc_x[i+1] = 7*(-1*y_differential_mask_nonzeros[i])
###inc_y[i+1] = 7*(x_differential_mask_nonzeros[i])
###elif abs_diff[i]!=0 and x_differential_mask_nonzeros[i]==0 and y_differential_mask_nonzeros[i]!=0:
###inc_x[i+1]= 12*(-1*y_differential_mask_nonzeros[i])
###elif abs_diff[i]!=0 and x_differential_mask_nonzeros[i]!=0 and y_differential_mask_nonzeros[i]==0:
###inc_y[i+1] = 12*(x_differential_mask_nonzeros[i])
###elif abs_diff[i]!=0 and abs_diff[i]>=3:
###if abs(x_differential[i])>abs(y_differential[i]):
###inc_y[i+1] = 12*(x_differential_mask_nonzeros[i])
###else:
###inc_x[i+1]= 12*(-1*y_differential_mask_nonzeros[i])
###else:
###inc_x[i+1] = 7*(-1*y_differential_mask_nonzeros[i])
###inc_y[i+1] = 7*(x_differential_mask_nonzeros[i])
###inc_x =list(inc_x)
###inc_x.append(inc_x[0])
@ -3908,6 +3943,98 @@ class Eynollah:
con_scaled[:,0, 1][con_scaled[:,0, 1]<0] = 0
con_scaled[:,0, 0][con_scaled[:,0, 0]<0] = 0
area_scaled = cv2.contourArea(con_scaled.astype(np.int32))
con_ind = con_ind.astype(np.int32)
results = [cv2.pointPolygonTest(con_ind, (con_scaled[ind,0, 0], con_scaled[ind,0, 1]), False) for ind in range(len(con_scaled[:,0, 1])) ]
results = np.array(results)
#print(results,'results')
results[results==0] = 1
diff_result = np.diff(results)
indices_2 = [ind for ind in range(len(diff_result)) if diff_result[ind]==2]
indices_m2 = [ind for ind in range(len(diff_result)) if diff_result[ind]==-2]
#print(area_scaled / area, "ratio")
#print(results,'results')
#if results[0]==1 and diff_result[-1]==-2:
##indices_2 = indices_2[1:]
##indices_m2 = indices_m2[1:]
#con_scaled[:indices_m2[0]+1,0, 1] = con_scaled[indices_m2[-1],0, 1]
#con_scaled[:indices_m2[0]+1,0, 0] = con_scaled[indices_m2[-1],0, 0]
#con_scaled[indices_2[-1]+1:,0, 1] = con_scaled[indices_m2[-1],0, 1]
#con_scaled[indices_2[-1]+1:,0, 0] = con_scaled[indices_m2[-1],0, 0]
#indices_2 = indices_2[:-1]
#indices_m2 = indices_m2[1:-1]
if results[0]==1:
con_scaled[:indices_m2[0]+1,0, 1] = con_ind[:indices_m2[0]+1,0,1]
con_scaled[:indices_m2[0]+1,0, 0] = con_ind[:indices_m2[0]+1,0,0]
#indices_2 = indices_2[1:]
indices_m2 = indices_m2[1:]
if len(indices_2)>len(indices_m2):
con_scaled[indices_2[-1]+1:,0, 1] = con_ind[indices_2[-1]+1:,0,1]
con_scaled[indices_2[-1]+1:,0, 0] = con_ind[indices_2[-1]+1:,0,0]
indices_2 = indices_2[:-1]
#diff_neg_pos = np.array(indices_m2) - np.array(indices_2)
#print(diff_neg_pos,'diff')
##print(indices_2, 'indices_2')
#indices_2 = np.array(indices_2)[diff_neg_pos>1]
#indices_m2 = np.array(indices_m2)[diff_neg_pos>1]
for ii in range(len(indices_2)):
#x_inner = con_ind[indices_2[ii]+1:indices_m2[ii]+1,0, 0]
#y_inner = con_ind[indices_2[ii]+1:indices_m2[ii]+1,0, 1]
#if x_inner[-1]>=x_inner[0]:
#x_interest = np.min(x_inner)
#else:
#x_interest = np.max(x_inner)
#if y_inner[-1]>=y_inner[0]:
#y_interest = np.min(y_inner)
#else:
#y_interest = np.max(y_inner)
con_scaled[indices_2[ii]+1:indices_m2[ii]+1,0, 1] = con_scaled[indices_2[ii],0, 1]
con_scaled[indices_2[ii]+1:indices_m2[ii]+1,0, 0] = con_scaled[indices_2[ii],0, 0]
#con_scaled[:,0, 1][results[:]>0] = con_ind[:,0,1][results[:]>0]
#con_scaled[:,0, 0][results[:]>0] = con_ind[:,0,0][results[:]>0]
#print(list(results), 'results')
#print(list(diff_result), 'diff_result')
#print(indices_2,'2')
#print(indices_m2,'-2')
#print(diff_neg_pos,'diff_neg_pos')
#con_scaled[:,0, 1] = gaussian_filter1d(con_scaled[:,0, 1], 0.1)
#con_scaled[:,0, 0] = gaussian_filter1d(con_scaled[:,0, 0], 0.1)
con_scaled[-1,0, 1] = con_scaled[0,0, 1]
con_scaled[-1,0, 0] = con_scaled[0,0, 0]
all_found_textline_polygons[j][:,0,1] = con_scaled[:,0, 1]
all_found_textline_polygons[j][:,0,0] = con_scaled[:,0, 0]
return all_found_textline_polygons

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