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How to use non_empty method in pandera
Best Python code snippet using pandera_python
evaluation.py
Source:evaluation.py 
1#!/usr/bin/env python3.52import numpy as np3from PIL import Image, ImageDraw4def two_d_iou(box, boxes):5 """Compute 2D IOU between a 2D bounding box 'box' and a list6 :param box: a numpy array in the form of [x1, y1, x2, y2] where (x1,y1) are7 image coordinates of the top-left corner of the bounding box, and (x2,y2)8 are the image coordinates of the bottom-right corner of the bounding box.9 :param boxes: a numpy array formed as a list of boxes in the form10 [[x1, y1, x2, y2], [x1, y1, x2, y2]].11 :return iou: a numpy array containing 2D IOUs between box and every element12 in numpy array boxes.13 """14 iou = np.zeros(len(boxes), np.float64)15 x1_int = np.maximum(box[0], boxes[:, 0])16 y1_int = np.maximum(box[1], boxes[:, 1])17 x2_int = np.minimum(box[2], boxes[:, 2])18 y2_int = np.minimum(box[3], boxes[:, 3])19 w_int = x2_int - x1_int20 h_int = y2_int - y1_int21 non_empty = np.logical_and(w_int > 0, h_int > 0)22 if non_empty.any():23 intersection_area = np.multiply(w_int[non_empty], h_int[non_empty])24 box_area = (box[2] - box[0]) * (box[3] - box[1])25 boxes_area = np.multiply(26 boxes[non_empty, 2] - boxes[non_empty, 0],27 boxes[non_empty, 3] - boxes[non_empty, 1])28 union_area = box_area + boxes_area - intersection_area29 iou[non_empty] = intersection_area / union_area30 return iou.round(3)31def two_half_d_iou(box, boxes):32 """Computes approximate 2.5D IOU on BEV between a 3D bounding box 'box' and a list33 of 3D bounding boxes 'boxes'. All boxes are assumed to be aligned with34 respect to gravity. Boxes are allowed to rotate only around their z-axis.35 :param box: a numpy array of the form: [ry, l, w, h, tx, ty, tz]36 :param boxes: a numpy array of the form:37 [[ry, l, h, w, tx, ty, tz], [ry, l, w, h, tx, ty, tz]]38 :return iou: a numpy array containing 3D IOUs between box and every element39 in numpy array boxes.40 """41 if len(boxes.shape) == 1:42 boxes = np.array([boxes])43 box_diag = np.sqrt(np.square(box[1]) +44 np.square(box[2])) / 245 boxes_diag = np.sqrt(np.square(boxes[:, 1]) +46 np.square(boxes[:, 2])) / 247 dist = np.sqrt(np.square(boxes[:, 4] - box[4]) +48 np.square(boxes[:, 6] - box[6]))49 non_empty = box_diag + boxes_diag >= dist50 iou = np.zeros(len(boxes), np.float64)51 if non_empty.any():52 # height_int, _ = height_metrics(box, boxes[non_empty])53 intersection = get_rectangular_metrics(box, boxes[non_empty])54 vol_box = np.prod(box[1:3])55 vol_boxes = np.prod(boxes[non_empty, 1:3], axis=1)56 union = vol_box + vol_boxes - intersection57 iou[non_empty] = intersection / union58 if iou.shape[0] == 1:59 iou = iou[0]60 return iou61def three_d_iou(box, boxes):62 """Computes approximate 3D IOU between a 3D bounding box 'box' and a list63 of 3D bounding boxes 'boxes'. All boxes are assumed to be aligned with64 respect to gravity. Boxes are allowed to rotate only around their z-axis.65 :param box: a numpy array of the form: [ry, l, w, h, tx, ty, tz]66 :param boxes: a numpy array of the form:67 [[ry, l, h, w, tx, ty, tz], [ry, l, w, h, tx, ty, tz]]68 :return iou: a numpy array containing 3D IOUs between box and every element69 in numpy array boxes.70 """71 # First, rule out boxes that do not intersect by checking if the spheres72 # which inscribes them intersect.73 if len(boxes.shape) == 1:74 boxes = np.array([boxes])75 box_diag = np.sqrt(np.square(box[1]) +76 np.square(box[2]) +77 np.square(box[3])) / 278 boxes_diag = np.sqrt(np.square(boxes[:, 1]) +79 np.square(boxes[:, 2]) +80 np.square(boxes[:, 3])) / 281 dist = np.sqrt(np.square(boxes[:, 4] - box[4]) +82 np.square(boxes[:, 5] - box[5]) +83 np.square(boxes[:, 6] - box[6]))84 non_empty = box_diag + boxes_diag >= dist85 iou = np.zeros(len(boxes), np.float64)86 if non_empty.any():87 height_int, _ = height_metrics(box, boxes[non_empty])88 rect_int = get_rectangular_metrics(box, boxes[non_empty])89 intersection = np.multiply(height_int, rect_int)90 vol_box = np.prod(box[1:4])91 vol_boxes = np.prod(boxes[non_empty, 1:4], axis=1)92 union = vol_box + vol_boxes - intersection93 iou[non_empty] = intersection / union94 if iou.shape[0] == 1:95 iou = iou[0]96 return iou97def height_metrics(box, boxes):98 """Compute 3D height intersection and union between a box and a list of99 boxes100 :param box: a numpy array of the form: [ry, l, h, w, tx, ty, tz]101 :param boxes: a numpy array of the form: [[ry, l, h, w, tx, ty, tz],.....102 [ry, l, h, w, tx, ty, tz]]103 :return height_intersection: a numpy array containing the intersection along104 the gravity axis between the two bbs105 :return height_union: a numpy array containing the union along the gravity106 axis between the two bbs107 """108 boxes_heights = boxes[:, 2]109 boxes_centroid_heights = boxes[:, 5]110 min_y_boxes = boxes_centroid_heights - boxes_heights111 max_y_box = box[5]112 min_y_box = box[5] - box[2]113 max_of_mins = np.maximum(min_y_box, min_y_boxes)114 min_of_maxs = np.minimum(max_y_box, boxes_centroid_heights)115 offsets = min_of_maxs - max_of_mins116 height_intersection = np.maximum(0, offsets)117 height_union = np.maximum(min_y_box, boxes_centroid_heights) \118 - np.minimum(min_y_box, min_y_boxes) - \119 np.maximum(0, -offsets)120 return height_intersection, height_union121def get_rotated_3d_bb(boxes):122 """Compute rotated 3D bounding box coordinates.123 :param boxes: a numpy array of the form: [[ry, l, h, w, tx, ty, tz],...124 [ry, l, h, w, tx, ty, tz]]125 :return x: x coordinates of the four corners required to describe a 3D126 bounding box arranged as [[x1, x2, x3, x4],127 [x1, x2, x3, x4],128 ... ]129 :return z: z coordinates of the four corners required to describe a 3D130 bounding box arranged as [[z1, z2, z3, z4],131 [z1, z2, z3, z4],132 ... ].133 """134 if len(boxes.shape) == 1:135 boxes = np.array([boxes])136 x = np.array([[]])137 z = np.array([[]])138 for i in boxes:139 rot_mat = np.array([[np.cos(i[0]), np.sin(i[0])],140 [-np.sin(i[0]), np.cos(i[0])]])141 x_corners = np.multiply(i[1] / 2, np.array([1, 1, -1, -1]))142 z_corners = np.multiply(i[3] / 2, np.array([1, -1, -1, 1]))143 temp_coor = np.dot(rot_mat, np.array([x_corners, z_corners]))144 # At the very first iteration, initialize x145 if x.shape[1] < 1:146 x = temp_coor[:1] + i[4]147 z = temp_coor[1:2] + i[6]148 # After that, append to the existing x149 else:150 x = np.append(x, temp_coor[:1] + i[4], axis=0)151 z = np.append(z, temp_coor[1:2] + i[6], axis=0)152 if x.shape[0] == 1:153 x = x[0]154 z = z[0]155 return x, z156def get_rectangular_metrics(box, boxes):157 """ Computes the intersection of the bases of oriented 3D bounding "box"158 and a set boxes of oriented 3D bounding boxes "boxes".159 :param box: a numpy array of the form: [ry, l, h, w, tx, ty, tz]160 :param boxes: a numpy array of the form: [[ry, l, h, w, tx, ty, tz],.....161 [ry, l, h, w, tx, ty, tz]]162 :return intersection: a numpy array containing intersection between the163 base of box and all other boxes.164 """165 if len(boxes.shape) == 1:166 boxes = np.array([boxes])167 mask_res = 0.01168 x_box, z_box = get_rotated_3d_bb(box)169 max_x_box = np.max(x_box)170 min_x_box = np.min(x_box)171 max_z_box = np.max(z_box)172 min_z_box = np.min(z_box)173 x_boxes, z_boxes = get_rotated_3d_bb(boxes)174 intersection = np.zeros(np.size(boxes, 0))175 if np.size(np.shape(x_boxes)) == 1:176 x_boxes = np.array([x_boxes])177 z_boxes = np.array([z_boxes])178 for i in range(np.size(boxes, 0)):179 x_i = x_boxes[i, :]180 z_i = z_boxes[i, :]181 test = max_x_box < np.min(x_i) or np.max(x_i) < min_x_box \182 or max_z_box < np.min(z_i) or np.max(z_i) < min_z_box183 if test:184 continue185 x_all = np.append(x_box, x_i)186 z_all = np.append(z_box, z_i)187 maxs = np.array([np.max(x_all), np.max(z_all)])188 mins = np.array([np.min(x_all), np.min(z_all)])189 mask_dims = np.int32(np.ceil((maxs - mins) / mask_res))190 mask_box_x = (x_box - mins[0]) / mask_res191 mask_box_z = (z_box - mins[1]) / mask_res192 mask_i_x = (x_i - mins[0]) / mask_res193 mask_i_z = (z_i - mins[1]) / mask_res194 # Drawing a binary image of the base of the two bounding boxes.195 # Then compute the element wise and of the two images to get the intersection.196 # Minor precision loss due to discretization.197 img = Image.new('L', (mask_dims[0], mask_dims[1]), 0)198 draw = ImageDraw.Draw(img, 'L')199 rect_coordinates = np.reshape(np.transpose(np.array([mask_box_x,200 mask_box_z])), 8)201 rect_coordinates = np.append(rect_coordinates, rect_coordinates[0:2])202 draw.polygon(rect_coordinates.ravel().tolist(), outline=255, fill=255)203 del draw204 mask_box = np.asarray(img)205 img2 = Image.new('L', (mask_dims[0], mask_dims[1]), 0)206 draw = ImageDraw.Draw(img2, 'L')207 i_coordinates = np.reshape(np.transpose(np.array([mask_i_x,208 mask_i_z])), 8)209 i_coordinates = np.append(i_coordinates, i_coordinates[0:2])210 draw.polygon(i_coordinates.ravel().tolist(), outline=255, fill=255)211 del draw212 mask_i = np.asarray(img2)213 mask_intersection = np.logical_and(mask_box, mask_i)214 intersection[i] = min(100, np.size(np.flatnonzero(215 mask_intersection)) * np.square(mask_res))216 if intersection.shape[0] == 1:217 intersection = intersection[0]...
Practica1MartinezBotet.py
Source:Practica1MartinezBotet.py
1from multiprocessing import Process2from multiprocessing import BoundedSemaphore, Semaphore, Lock3from multiprocessing import current_process4from multiprocessing import Value, Array, Queue5from time import sleep6from random import random, randint7"N es cuanto produce cada uno"8N = 209K = 310NPROD = 311NCONS = 112def delay(factor = 3):13 sleep(random()/factor)14"index es a quien le toca"15def add_data(storage, data, pid, mutex):16 mutex.acquire()17 try:18 storage[pid] = randint(0,5) + data.value19 delay(6)20 finally:21 mutex.release()22"Cogemos el dato y lo cambiamos por 0, la idea del bucle es que te devuleve el min y la pos"23def get_data(storage,mutex,data):24 mutex.acquire()25 print(storage[0],storage[1],storage[2])26 i=127 m=storage[0]28 pos=029 while m==-1:30 m=storage[i]31 pos=i32 i=i+133 try:34 for i,c in enumerate(storage):35 if c<m and c!=-1:36 m=c37 pos=i38 data.value=m39 storage[pos]=040 finally:41 mutex.release()42 return data.value,pos43""44def producer(storage, empty, non_empty, mutex,data):45 for v in range(N):46 print (f"producer {current_process().name} produciendo")47 pid=int(current_process().name.split('_')[1])48 delay(6)49 empty[pid].acquire()50 try:51 add_data(storage,data, pid,52 mutex)53 finally: 54 non_empty[pid].release()55 print (f"producer {current_process().name} almacenado {v}")56 empty[pid].acquire()57 storage[pid]=-158 non_empty[pid].release()59 60def hay_productor(storage):61 res=False62 i=063 while i<len(storage) and not(res):64 if storage[i]!=-1:65 res=True66 i=i+167 return res68def consumer(storage, data, empty, non_empty, mutex):69 l=[]70 for i in non_empty:71 i.acquire()72 while hay_productor(storage):73 valor,pos=get_data(storage,mutex,data)74 l.append(valor)75 empty[pos].release()76 non_empty[pos].acquire()77 print("Ya no hay productores")78 print(l)79def main():80 storage = Array('i', K)81 data=Value('i',0)82 for i in range(K):83 storage[i] = 084 #print ("almacen inicial", storage[:], "indice", index.value)85 non_empty = [Semaphore(0) for _ in range(NPROD)]86 empty = [Lock() for _ in range(NPROD)]87 mutex = Lock()88 prodlst = [ Process(target=producer,89 name=f'prod_{i}',90 args=(storage, empty, non_empty, mutex,data))91 for i in range(NPROD) ]92 conslst = [ Process(target=consumer,93 name=f"cons_{i}",94 args=(storage, data,empty, non_empty, mutex))]95 for p in prodlst + conslst:96 p.start()97 for p in prodlst + conslst:98 p.join()99 100if __name__ == '__main__':...
analyze.py
Source:analyze.py
1#!/usr/bin/env python2__author__ = 'greg'3import os4import cPickle as pickle5# for Greg - which computer am I on?6if os.path.exists("/home/ggdhines"):7 base_directory = "/home/ggdhines"8 code_directory = base_directory + "/github"9elif os.path.exists("/Users/greg"):10 base_directory = "/Users/greg"11 code_directory = base_directory + "/Code"12else:13 base_directory = "/home/greg"14 code_directory = base_directory + "/github"15results = pickle.load(open(base_directory+"/Databases/serengeti/results.pickle","rb"))16skipped = 017non_empty = 018for zooniverse_id in results:19 status = results[zooniverse_id]["status"]20 if status == "skipped":21 skipped += 122 continue23 classification = results[zooniverse_id]["name"]24 if "deer" in classification:25 non_empty += 126 elif "hyena" in classification:27 non_empty += 128 elif ("wildebeest" in classification) or ("wildebeast" in classification):29 non_empty += 130 elif "zebra" in classification:31 non_empty += 132 elif "impala" in classification:33 non_empty += 134 elif "gazelle" in classification:35 non_empty += 136 elif "buffalo" in classification:37 non_empty += 138 elif "elephant" in classification:39 non_empty += 140 elif "animal" in classification:41 non_empty += 142 elif "lion" in classification:43 non_empty += 144 elif ("aardvark" in classification) or ("aadvark" in classification):45 non_empty += 146 elif "horse" in classification:47 non_empty += 148 elif ("birds" in classification) or ("bird" in classification):49 non_empty += 150 elif "oryx" in classification:51 non_empty += 152 elif "antelope" in classification:53 non_empty += 154 elif "emu" in classification:55 non_empty += 156 elif "fowl" in classification:57 non_empty += 158 elif ("suv" in classification) or ("rover" in classification) or ("vehicle" in classification):59 non_empty += 160 elif "peacock" in classification:61 non_empty += 162 elif "dikdik" in classification:63 non_empty += 164 elif "giraffe" in classification:65 non_empty += 166 elif "bull" in classification:67 non_empty += 168 elif ("jeans" in classification) or ("board" in classification) or ("pants" in classification) or ("jacket" in classification):69 non_empty += 170 elif "cow" in classification:71 non_empty += 172 elif "warthog" in classification:73 non_empty += 174 elif "baboon" in classification:75 non_empty += 176 elif "mammal" in classification:77 non_empty += 178 elif "boar" in classification:79 non_empty += 180 else:81 print classification...
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