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| from __future__ import absolute_import |
| from __future__ import division |
| from __future__ import print_function |
|
|
| import numpy as np |
|
|
| import os |
| import sys |
|
|
| __dir__ = os.path.dirname(os.path.abspath(__file__)) |
| sys.path.append(__dir__) |
| sys.path.insert(0, os.path.abspath(os.path.join(__dir__, ".."))) |
|
|
| os.environ["FLAGS_allocator_strategy"] = "auto_growth" |
|
|
| import cv2 |
| import json |
| import paddle |
|
|
| from ppocr.data import create_operators, transform |
| from ppocr.modeling.architectures import build_model |
| from ppocr.postprocess import build_post_process |
| from ppocr.utils.save_load import load_model |
| from ppocr.utils.utility import get_image_file_list |
| import tools.program as program |
| from PIL import Image, ImageDraw, ImageFont |
| import math |
|
|
|
|
| def draw_e2e_res_for_chinese( |
| image, boxes, txts, config, img_name, font_path="./doc/simfang.ttf" |
| ): |
| h, w = image.height, image.width |
| img_left = image.copy() |
| img_right = Image.new("RGB", (w, h), (255, 255, 255)) |
|
|
| import random |
|
|
| random.seed(0) |
| draw_left = ImageDraw.Draw(img_left) |
| draw_right = ImageDraw.Draw(img_right) |
| for idx, (box, txt) in enumerate(zip(boxes, txts)): |
| box = np.array(box) |
| box = [tuple(x) for x in box] |
| color = (random.randint(0, 255), random.randint(0, 255), random.randint(0, 255)) |
| draw_left.polygon(box, fill=color) |
| draw_right.polygon(box, outline=color) |
| font = ImageFont.truetype(font_path, 15, encoding="utf-8") |
| draw_right.text([box[0][0], box[0][1]], txt, fill=(0, 0, 0), font=font) |
| img_left = Image.blend(image, img_left, 0.5) |
| img_show = Image.new("RGB", (w * 2, h), (255, 255, 255)) |
| img_show.paste(img_left, (0, 0, w, h)) |
| img_show.paste(img_right, (w, 0, w * 2, h)) |
|
|
| save_e2e_path = os.path.dirname(config["Global"]["save_res_path"]) + "/e2e_results/" |
| if not os.path.exists(save_e2e_path): |
| os.makedirs(save_e2e_path) |
| save_path = os.path.join(save_e2e_path, os.path.basename(img_name)) |
| cv2.imwrite(save_path, np.array(img_show)[:, :, ::-1]) |
| logger.info("The e2e Image saved in {}".format(save_path)) |
|
|
|
|
| def draw_e2e_res(dt_boxes, strs, config, img, img_name): |
| if len(dt_boxes) > 0: |
| src_im = img |
| for box, str in zip(dt_boxes, strs): |
| box = box.astype(np.int32).reshape((-1, 1, 2)) |
| cv2.polylines(src_im, [box], True, color=(255, 255, 0), thickness=2) |
| cv2.putText( |
| src_im, |
| str, |
| org=(int(box[0, 0, 0]), int(box[0, 0, 1])), |
| fontFace=cv2.FONT_HERSHEY_COMPLEX, |
| fontScale=0.7, |
| color=(0, 255, 0), |
| thickness=1, |
| ) |
| save_det_path = ( |
| os.path.dirname(config["Global"]["save_res_path"]) + "/e2e_results/" |
| ) |
| if not os.path.exists(save_det_path): |
| os.makedirs(save_det_path) |
| save_path = os.path.join(save_det_path, os.path.basename(img_name)) |
| cv2.imwrite(save_path, src_im) |
| logger.info("The e2e Image saved in {}".format(save_path)) |
|
|
|
|
| def main(): |
| global_config = config["Global"] |
|
|
| |
| model = build_model(config["Architecture"]) |
|
|
| load_model(config, model) |
|
|
| |
| post_process_class = build_post_process(config["PostProcess"], global_config) |
|
|
| |
| transforms = [] |
| for op in config["Eval"]["dataset"]["transforms"]: |
| op_name = list(op)[0] |
| if "Label" in op_name: |
| continue |
| elif op_name == "KeepKeys": |
| op[op_name]["keep_keys"] = ["image", "shape"] |
| transforms.append(op) |
|
|
| ops = create_operators(transforms, global_config) |
|
|
| save_res_path = config["Global"]["save_res_path"] |
| if not os.path.exists(os.path.dirname(save_res_path)): |
| os.makedirs(os.path.dirname(save_res_path)) |
|
|
| model.eval() |
| with open(save_res_path, "wb") as fout: |
| for file in get_image_file_list(config["Global"]["infer_img"]): |
| logger.info("infer_img: {}".format(file)) |
| with open(file, "rb") as f: |
| img = f.read() |
| data = {"image": img} |
| batch = transform(data, ops) |
| images = np.expand_dims(batch[0], axis=0) |
| shape_list = np.expand_dims(batch[1], axis=0) |
| images = paddle.to_tensor(images) |
| preds = model(images) |
| post_result = post_process_class(preds, shape_list) |
| points, strs = post_result["points"], post_result["texts"] |
| |
| dt_boxes_json = [] |
| for poly, str in zip(points, strs): |
| tmp_json = {"transcription": str} |
| tmp_json["points"] = poly.tolist() |
| dt_boxes_json.append(tmp_json) |
| otstr = file + "\t" + json.dumps(dt_boxes_json) + "\n" |
| fout.write(otstr.encode()) |
| src_img = cv2.imread(file) |
| if global_config["infer_visual_type"] == "EN": |
| draw_e2e_res(points, strs, config, src_img, file) |
| elif global_config["infer_visual_type"] == "CN": |
| src_img = Image.fromarray(cv2.cvtColor(src_img, cv2.COLOR_BGR2RGB)) |
| draw_e2e_res_for_chinese( |
| src_img, |
| points, |
| strs, |
| config, |
| file, |
| font_path="./doc/fonts/simfang.ttf", |
| ) |
|
|
| logger.info("success!") |
|
|
|
|
| if __name__ == "__main__": |
| config, device, logger, vdl_writer = program.preprocess() |
| main() |
|
|