Ludovic CASTIGLIA
4 months ago
parent
5ed4051a8e
commit
604874c029
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After Width: | Height: | Size: 267 KiB |
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from matplotlib.widgets import RectangleSelector
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import matplotlib.pyplot as plt
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from random import randint
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import numpy as np
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def doPatchMatch(img,x1,y1,x2,y2,patchSize=129):
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def getDist(pValue1, pValue2):
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return np.sum((pValue1 - pValue2) ** 2)
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def initializePermimiter(finish=False):
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perimeter = []
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for x in range(x1, x2 + 1):
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perimeter.append((x, y1))
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perimeter.append((x, y2))
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if finish:
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perimeter.append((x,y1-1))
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perimeter.append((x,y2+1))
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for y in range(y1 + 1, y2):
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perimeter.append((x1, y))
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perimeter.append((x2, y))
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if finish:
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perimeter.append((x1-1,y))
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perimeter.append((x2+1,y))
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return np.array(perimeter)
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def getRandomPatchFromPerimiter(perimiter):
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x,y = perimiter[np.random.randint(len(perimiter))]
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patch = np.array([[i, j] for i in range(x - semiPatch, x + semiPatch + 1)
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for j in range(y - semiPatch, y + semiPatch + 1)])
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return patch
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def getZoneMask(zoneValue,outside):
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mask = []
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for value in zoneValue:
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mask.append((value.sum() == 0) ^outside)
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return np.array(mask)
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def applyMask(patch,mask,oposed=False):
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return patch[mask^oposed]
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def getValueFromPatch(patch):
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ret = img[patch[0][1]:patch[0][1]+patchSize,patch[0][0]:patch[0][0]+patchSize]
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ret = ret.transpose(1, 0, 2)
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return ret.reshape(-1, 3)
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def getRandomPatch(patchCoordFound):
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if (len(patchCoordFound) == 0):
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#TODO peut être trouver un patch autour du trou et verrifier que pas dans le trou
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x = randint(semiPatch,width-semiPatch-1)
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y = randint(semiPatch,height-semiPatch-1)
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patch = np.array([[i, j] for i in range(x - semiPatch, x + semiPatch + 1)
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for j in range(y - semiPatch, y + semiPatch + 1)])
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else:
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patch = patchCoordFound[randint(0,len(patchCoordFound)-1)]
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return patch
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def getBestNeigbourPatch(zoneMask,filteredZoneValue,dist,patch,offset):
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voisin = [[-1,-1],[-1,0],[0,-1],[0,0],[1,-1],[-1,1],[0,1],[1,0],[1,1]]
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found = False
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bPatch = []
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for x,y in voisin:
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nPatch = patch.copy()
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nPatch[:,0] += x*offset
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nPatch[:,1] += y*offset
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if np.any(nPatch < 0) or np.any(nPatch[:,0] >= width) or np.any(nPatch[:,1] >= height):
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#TODO verrifier que le patch est pas dans le troue si non ff
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continue
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nPatchValue = getValueFromPatch(nPatch)
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filteredPatchValue = applyMask(nPatchValue,zoneMask)
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nDist = getDist(filteredZoneValue,filteredPatchValue)
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if (nDist < dist):
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dist = nDist
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bPatch = nPatch
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found = True
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return found,bPatch,dist
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def getBestPatchForZone(zoneValue,zoneMask,patchCoordFound):
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filteredZoneValue = applyMask(zoneValue,zoneMask)
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patch = getRandomPatch(patchCoordFound)
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patchValue = getValueFromPatch(patch)
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filteredPatchValue = applyMask(patchValue,zoneMask)
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dist = getDist(filteredZoneValue,filteredPatchValue)
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offset = 1
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while offset < min(width,height)/2:
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found, nPatch,nDist = getBestNeigbourPatch(zoneMask,filteredZoneValue,dist,patch,offset)
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if (found):
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patch = nPatch
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dist = nDist
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offset = 1
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else:
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offset*=2
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patchCoordFound.append(patch)
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return patchValue
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def applyPatch(filteredZone,zoneMask, patchValue):
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filteredPatchValue = applyMask(patchValue,zoneMask,True)
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for i in range(len(filteredZone)) :
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img[filteredZone[i][1],filteredZone[i][0]] = filteredPatchValue[i]
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def updatePerimiter(filteredZone,perimiter):
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for x,y in filteredZone:
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if ((x,y) in filteredZone):
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perimiter = np.delete(perimiter, np.where((perimiter == [x, y]).all(axis=1))[0], axis=0)
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voisin = [[-1,-1],[-1,0],[0,-1],[0,0],[1,-1],[-1,1],[0,1],[1,0],[1,1]]
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for x,y in filteredZone:
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for offsetx,offsety in voisin:
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if img[y+offsety,x+offsetx].sum() == 0:
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perimiter = np.vstack((perimiter, [x+offsetx, y+offsety]))
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return perimiter
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def addEdge(edges,zone):
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# pas des deux coté car zone pas filteredZone pour endroit biscornue
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x,y = zone[0]
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for xx in range(x,x+patchSize):
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if x1<=xx<=x2:
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if y1<=y<=y2:
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edges.append([xx,y])
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if y1<=y+patchSize<=y2:
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edges.append([xx,y+patchSize])
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for yy in range(y,y+patchSize):
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if y1<=yy<=y2:
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if x1<=x<=x2:
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edges.append([x,yy])
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if x1<=x+patchSize<=x2:
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edges.append([x+patchSize,yy])
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return edges
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def smoothEdges(edges):
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perimiter = initializePermimiter(True)
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edges.extend(perimiter.tolist())
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edges = np.array(edges)
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offsets = np.array([[-1,-1],[-1,0],[-1,1],[0,-1],[0,1],[1,-1],[1,0],[1,1]])
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for edge in edges:
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neighbors = edge + offsets[:,None]
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neighbors = neighbors.reshape(-1,2)
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valid_neighbors = neighbors[
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(neighbors[:,0] >= 0) & (neighbors[:,0] < width) &
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(neighbors[:,1] >= 0) & (neighbors[:,1] < height)
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]
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if len(valid_neighbors) > 0:
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neighbor_values = img[valid_neighbors[:,1], valid_neighbors[:,0]]
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avg_value = np.mean(neighbor_values, axis=0)
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img[edge[1], edge[0]] = avg_value
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# for x,y in edges:
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# img[y,x] = [255,0,0]
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semiPatch = int(patchSize/2)
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height, width, _ = img.shape
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patchCoordFound = []
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edges = []
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perimiter = initializePermimiter()
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img[y1:y2+1, x1:x2+1] = 0
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it = 0
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while len(perimiter)> 0:
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zone = getRandomPatchFromPerimiter(perimiter)
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edges = addEdge(edges,zone)
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zoneValue = getValueFromPatch(zone)
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zoneMask = getZoneMask(zoneValue,True)
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filteredZoneInside = applyMask(zone,zoneMask,True)
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patchValue = getBestPatchForZone(zoneValue,zoneMask,patchCoordFound)
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applyPatch(filteredZoneInside,zoneMask,patchValue)
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perimiter = updatePerimiter(filteredZoneInside,perimiter)
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it +=1
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print(it)
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print("smoothing edges")
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smoothEdges(edges)
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return img
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img = plt.imread('asset/vache.png')
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if img.dtype == np.float32:
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img = (img * 255).astype(np.uint8)
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img = img[:,:,0:3]
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def onselect(eclick, erelease):
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x1, y1 = eclick.xdata, eclick.ydata
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x2, y2 = erelease.xdata, erelease.ydata
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print("drawing")
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img_copy = np.copy(img)
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res = doPatchMatch(img_copy,int(x1),int(y1),int(x2),int(y2))
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ax.imshow(res)
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plt.draw()
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print("drawed")
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fig, ax = plt.subplots()
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ax.imshow(img)
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toggle_selector = RectangleSelector(ax, onselect, useblit=True,
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button=[1], minspanx=5, minspany=5, spancoords='pixels',
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interactive=True)
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plt.axis('off')
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plt.show()
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