diff --git a/app.py b/app.py deleted file mode 100644 index ababac3..0000000 --- a/app.py +++ /dev/null @@ -1,75 +0,0 @@ -import torch -from flask import Flask, request -import torch.nn as nn -import pickle -import jieba - -app = Flask(__name__) -# 初始化模型 -result = "" - - -class Model(nn.Module): - def __init__(self): - super(Model, self).__init__() - self.embedding = nn.Embedding(10002, 300, padding_idx=10001) - self.lstm = nn.LSTM(300, 128, 2, bidirectional=True, batch_first=True, dropout=0.5) - self.fc = nn.Linear(128 * 2, 2) - - def forward(self, x): - x, _ = x - out = self.embedding(x) # [batch_size, seq_len, embeding]=[128, 32, 300] - out, _ = self.lstm(out) - out = self.fc(out[:, -1, :]) # 句子最后时刻的 hidden state - return out - - -model = Model() -model.load_state_dict(torch.load('./THUCNews/saved_dict/TextRNN.ckpt', map_location=torch.device("cpu"))) -model.eval() -stopwords = open('./THUCNews/data/hit_stopwords.txt', encoding='utf8').read().split('\n')[:-1] - -vocab = pickle.load(open('./THUCNews/data/vocab.pkl', 'rb')) -classes = ['negative', 'positive'] - -s = '空调吵，住在电梯旁，电梯门口放垃圾箱，极臭，布草间没关门，也臭，臭到房间里，门下塞毛巾也挡不住臭味，开窗外面吵，关窗空调吵，楼下早餐桌子上摆满垃圾没人整理，不能再差的体验了' - - -# s = '东东还算不错。重装系统时，网上查不到怎么修改BIOS，才能安装？问题请帮忙解决！' - - -@app.route('/api/content', methods=["POST"]) -def content(): - get_json = request.get_json() - global model - global result - global classes - result = "" - s = get_json.get("content")[0] - print(6777, s) - try: - s = list(jieba.lcut(s)) - s = [i for i in s if i not in stopwords] - s = [vocab.get(i, 10000) for i in s] - if len(s) > 64: - s = s[:64] - else: - for i in range(64 - len(s)): - s.append(vocab['']) - - outputs = model((torch.LongTensor(s).unsqueeze(0), None)) - print(torch.argmax(outputs)) - result = classes[torch.argmax(outputs)] - except Exception as e: # 未捕获到异常，程序直接报错 - result = e - return "pridicting" - - -@app.route('/api/model_res', methods=['GET']) -def model_res(): - global result - return str(result) - - -if __name__ == '__main__': - app.run(host="127.0.0.1", port=8006) diff --git a/front/package-lock.json b/front/package-lock.json index 4098b92..1f7cf0f 100644 --- a/front/package-lock.json +++ b/front/package-lock.json @@ -9,8 +9,10 @@ "version": "0.0.0", "dependencies": { "axios": "^1.6.8", + "dayjs": "^1.11.11", "element-plus": "^2.7.2", "lodash": "^4.17.21", + "nprogress": "^0.2.0", "vue": "^3.4.21" }, "devDependencies": { @@ -1522,6 +1524,11 @@ "resolved": "https://registry.npmmirror.com/normalize-wheel-es/-/normalize-wheel-es-1.2.0.tgz", "integrity": "sha512-Wj7+EJQ8mSuXr2iWfnujrimU35R2W4FAErEyTmJoJ7ucwTn2hOUSsRehMb5RSYkxXGTM7Y9QpvPmp++w5ftoJw==" }, + "node_modules/nprogress": { + "version": "0.2.0", + "resolved": "https://registry.npmmirror.com/nprogress/-/nprogress-0.2.0.tgz", + "integrity": "sha512-I19aIingLgR1fmhftnbWWO3dXc0hSxqHQHQb3H8m+K3TnEn/iSeTZZOyvKXWqQESMwuUVnatlCnZdLBZZt2VSA==" + }, "node_modules/path-parse": { "version": "1.0.7", "resolved": "https://registry.npmmirror.com/path-parse/-/path-parse-1.0.7.tgz", diff --git a/front/package.json b/front/package.json index 6897f3e..cb7ae0c 100644 --- a/front/package.json +++ b/front/package.json @@ -10,8 +10,10 @@ }, "dependencies": { "axios": "^1.6.8", + "dayjs": "^1.11.11", "element-plus": "^2.7.2", "lodash": "^4.17.21", + "nprogress": "^0.2.0", "vue": "^3.4.21" }, "devDependencies": { diff --git a/front/src/App copy.vue b/front/src/App copy.vue new file mode 100644 index 0000000..524c89e --- /dev/null +++ b/front/src/App copy.vue @@ -0,0 +1,226 @@ + + + + + diff --git a/front/src/App.vue b/front/src/App.vue index 5fefa16..9e59626 100644 --- a/front/src/App.vue +++ b/front/src/App.vue @@ -1,50 +1,106 @@ diff --git a/front/src/assets/config/imgconf.json b/front/src/assets/config/imgconf.json deleted file mode 100644 index 367f4de..0000000 --- a/front/src/assets/config/imgconf.json +++ /dev/null @@ -1,6 +0,0 @@ -[ - { - "label": "f1-score", - "path": "assets/imgs/bilstm/1.png" - } -] \ No newline at end of file diff --git a/front/src/assets/imgs/bilstm/1.png b/front/src/assets/imgs/bilstm/1.png deleted file mode 100644 index 5768d2b..0000000 Binary files a/front/src/assets/imgs/bilstm/1.png and /dev/null differ diff --git a/front/src/main.js b/front/src/main.js index 76b0267..ee17cef 100644 --- a/front/src/main.js +++ b/front/src/main.js @@ -9,5 +9,5 @@ import axios from "axios" const app = createApp(App) app.config.globalProperties.$_ = _ app.config.globalProperties.$axios = axios -app.use(ElementPlus) +app.use(ElementPlus, { size: "large" }) app.mount('#app') \ No newline at end of file diff --git a/front/src/style.css b/front/src/style.css index 4dc4eeb..f5a0728 100644 --- a/front/src/style.css +++ b/front/src/style.css @@ -2,4 +2,21 @@ html, body { margin: 0; padding: 0; + font-size: 1.2em; } + +#nprogress .bar { + background: #79bbff !important; + height: 6px; +} + +.el-descriptions__body .el-descriptions__table .el-descriptions__cell { + font-size: 3em !important; + height: 64px; +} + +.el-tag--large { + font-size: 26px; + line-height: 30px; + height: 48px; +} \ No newline at end of file diff --git a/front/vite600.zip b/front/vite600.zip deleted file mode 100644 index 789d2c8..0000000 Binary files a/front/vite600.zip and /dev/null differ diff --git a/inference copy.py b/inference copy.py new file mode 100644 index 0000000..0d7b884 --- /dev/null +++ b/inference copy.py @@ -0,0 +1,161 @@ +import cv2 +import torch +import numpy as np +from PIL import Image +from ultralytics import YOLO +from flask import Flask, request, send_file, make_response +from flask_cors import CORS +import time +from io import BytesIO + +# 3个输入参数 +img_path = "img0002.jpg" +iou = 0.1 +conf = 0.25 +originalImgPath = "" +result1Path = "" +result2Path = "" + +app = Flask(__name__) +# 解决跨域问题 +cors = CORS( + app, + resources={ + r"/api/*": { + "origins": ["http://localhost:5173"], + "methods": ["GET", "POST"], + } + }, +) +# 初始化模型 +resResult = "" + + +def split_image(img_path, size=(800, 800)): + img = cv2.imread(img_path) + height, width = img.shape[:2] + rows = (height + size[1] - 1) // size[1] + cols = (width + size[0] - 1) // size[0] + img_list = [] + indexes = [] + for r in range(rows): + for c in range(cols): + y1 = r * size[1] + y2 = min((r + 1) * size[1], height) + x1 = c * size[0] + x2 = min((c + 1) * size[0], width) + split = img[y1:y2, x1:x2] + img_list.append(split) + indexes.append((r, c)) + return img_list, indexes, (height, width) + + +def combine_images(pred_imgs, indexes, size=(800, 800), img_shape=(3000, 4000)): + combined_img = np.zeros((img_shape[0], img_shape[1], 3), dtype=np.uint8) + for idx, (r, c) in enumerate(indexes): + y1 = r * size[1] + y2 = min((r + 1) * size[1], img_shape[0]) + x1 = c * size[0] + x2 = min((c + 1) * size[0], img_shape[1]) + combined_img[y1:y2, x1:x2] = pred_imgs[idx][: y2 - y1, : x2 - x1] + return combined_img + + +follicle_groups_detector = YOLO("follicle_groups.pt") +follicles_detector = YOLO("follicles.pt") + + +# 保存检测图片 +@app.route("/api/checkPng", methods=["POST"]) +def checkPng(): + global follicle_groups_detector + global follicles_detector + global originalImgPath + global result1Path + global result2Path + global resResult + pngFile = request.files["file"] + img = Image.open(pngFile.stream) + iou = request.form.get("iou") + iou = float(iou) + conf = request.form.get("conf") + conf = float(conf) + nowtime1 = time.strftime("%Y-%m-%d_%H-%M-%S", time.localtime(time.time())) + originalImgPath = "images/original" + str(nowtime1) + ".png" + result1Path = "images/result1" + str(nowtime1) + ".png" + result2Path = "images/result2" + str(nowtime1) + ".png" + img.save(originalImgPath) + results = follicle_groups_detector(originalImgPath, iou=iou, conf=conf) + for r in results: + num_follicle_groups = len(r.boxes) + im_array = r.plot() + im = Image.fromarray(im_array[..., ::-1]) + im.save(result1Path) # 输出结果图1 + + img_list, indexes, (height, width) = split_image(result1Path) + print(f"Number of image blocks: {len(img_list)}") + num_small_follicles = 0 + num_big_follicles = 0 + pred_imgs = [] + for img in img_list: + results = follicles_detector(img, iou=iou, conf=conf) + for r in results: + num_small_follicles += torch.sum(r.boxes.cls == 0).item() + num_big_follicles += torch.sum(r.boxes.cls == 1).item() + im_array = r.plot() + pred_imgs.append(im_array) + + # 输出的3个结果文本 + print("毛囊群数量：", num_follicle_groups) + print("大毛囊数量：", num_big_follicles) + print("小毛囊数量：", num_small_follicles) + + combined_img = combine_images( + pred_imgs, indexes, size=(800, 800), img_shape=(height, width) + ) + combined_image_pil = Image.fromarray(combined_img[..., ::-1]) + combined_image_pil.save(result2Path) # 输出结果图2 + resResult = { + "hasError": False, + "num_follicle_groups": num_follicle_groups, + "num_big_follicles": num_big_follicles, + "num_small_follicles": num_small_follicles, + "originalImgPath": originalImgPath, + "result1Path": result1Path, + "result2Path": result2Path, + } + return resResult + + +# 检测结果返回 +@app.route("/api/checkResult", methods=["GET"]) +def checkResult(): + global resResult + return resResult + + +# 图片查询 +@app.route("/api/getPng/", methods=["GET"]) +def getPng(pngPath): + # 打开或处理图像 + img = Image.open("images/" + pngPath) + # 对图像进行处理，例如调整大小 + img = img.resize((800, 600)) + # 创建一个 BytesIO 对象来保存图像数据 + img_byte_arr = BytesIO() + img.save(img_byte_arr, format="PNG") + img_byte_arr.seek(0) + + # 使用 send_file 返回图像数据 + # return send_file(img_byte_arr, mimetype='image/jpeg') + + # 或者使用 make_response 来创建一个响应对象 + response = make_response(img_byte_arr.getvalue()) + response.headers.set("Content-Type", "image/jpeg") + response.headers.set("Content-Disposition", "attachment", filename=pngPath) + + return response + + +if __name__ == "__main__": + app.run(host="127.0.0.1", port=8006, debug=True) diff --git a/inference.py b/inference.py index 7a9cfb6..f5753df 100644 --- a/inference.py +++ b/inference.py @@ -3,12 +3,33 @@ import torch import numpy as np from PIL import Image from ultralytics import YOLO - +from flask import Flask, request, send_file, make_response +from flask_cors import CORS +import time +from io import BytesIO # 3个输入参数 -img_path = 'img0002.jpg' +img_path = "img0002.jpg" iou = 0.1 conf = 0.25 +originalImgPath = "" +result1Path = "" +result2Path = "" +nowtime1 = time.strftime("%Y-%m-%d_%H-%M-%S", time.localtime(time.time())) +app = Flask(__name__) +# 解决跨域问题 +cors = CORS( + app, + resources={ + r"/api/*": { + "origins": ["http://localhost:5173"], + "methods": ["GET", "POST"], + } + }, +) +# 初始化模型 +resResult = "" + def split_image(img_path, size=(800, 800)): img = cv2.imread(img_path) @@ -36,46 +57,118 @@ def combine_images(pred_imgs, indexes, size=(800, 800), img_shape=(3000, 4000)): y2 = min((r + 1) * size[1], img_shape[0]) x1 = c * size[0] x2 = min((c + 1) * size[0], img_shape[1]) - combined_img[y1:y2, x1:x2] = pred_imgs[idx][:y2 - y1, :x2 - x1] + combined_img[y1:y2, x1:x2] = pred_imgs[idx][: y2 - y1, : x2 - x1] return combined_img -follicle_groups_detector = YOLO('follicle_groups.pt') -follicles_detector = YOLO('follicles.pt') - -results = follicle_groups_detector(img_path, iou=iou, conf=conf) -for r in results: - num_follicle_groups = len(r.boxes) - im_array = r.plot() - im = Image.fromarray(im_array[..., ::-1]) - im.save('results_1.jpg') #输出结果图1 - -img_list, indexes, (height, width) = split_image(img_path) -print(f"Number of image blocks: {len(img_list)}") -num_small_follicles = 0 -num_big_follicles = 0 -pred_imgs = [] -for img in img_list: - results = follicles_detector(img, iou=iou, conf=conf) + +follicle_groups_detector = YOLO("follicle_groups.pt") +follicles_detector = YOLO("follicles.pt") + + +# 保存图片 +@app.route("/api/savePng", methods=["POST"]) +def savePng(): + global nowtime1 + global originalImgPath + nowtime1 = time.strftime("%Y-%m-%d_%H-%M-%S", time.localtime(time.time())) + pngFile = request.files["file"] + img = Image.open(pngFile.stream) + originalImgPath = "images/original" + str(nowtime1) + ".png" + img.save(originalImgPath) + resResult = { + "hasError": False, + "originalImgPath": originalImgPath, + } + return resResult + + +# 检测图片 +@app.route("/api/checkPng", methods=["POST"]) +def checkPng(): + global follicle_groups_detector + global follicles_detector + global originalImgPath + global nowtime1 + global result1Path + global result2Path + global resResult + iou = request.form.get("iou") + iou = float(iou) + conf = request.form.get("conf") + conf = float(conf) + result1Path = "images/result1" + str(nowtime1) + ".png" + result2Path = "images/result2" + str(nowtime1) + ".png" + results = follicle_groups_detector(originalImgPath, iou=iou, conf=conf) for r in results: - num_small_follicles += torch.sum(r.boxes.cls == 0).item() - num_big_follicles += torch.sum(r.boxes.cls == 1).item() + num_follicle_groups = len(r.boxes) im_array = r.plot() - pred_imgs.append(im_array) - -# 输出的3个结果文本 -print('毛囊群数量：', num_follicle_groups) -print('大毛囊数量：', num_big_follicles) -print('小毛囊数量：', num_small_follicles) - -combined_img = combine_images(pred_imgs, indexes, size=(800, 800), img_shape=(height, width)) -combined_image_pil = Image.fromarray(combined_img[..., ::-1]) -combined_image_pil.save('results_2.jpg') #输出结果图2 - - - - - - - - - + im = Image.fromarray(im_array[..., ::-1]) + im.save(result1Path) # 输出结果图1 + + img_list, indexes, (height, width) = split_image(result1Path) + print(f"Number of image blocks: {len(img_list)}") + num_small_follicles = 0 + num_big_follicles = 0 + pred_imgs = [] + for img in img_list: + results = follicles_detector(img, iou=iou, conf=conf) + for r in results: + num_small_follicles += torch.sum(r.boxes.cls == 0).item() + num_big_follicles += torch.sum(r.boxes.cls == 1).item() + im_array = r.plot() + pred_imgs.append(im_array) + + # 输出的3个结果文本 + print("毛囊群数量：", num_follicle_groups) + print("大毛囊数量：", num_big_follicles) + print("小毛囊数量：", num_small_follicles) + + combined_img = combine_images( + pred_imgs, indexes, size=(800, 800), img_shape=(height, width) + ) + combined_image_pil = Image.fromarray(combined_img[..., ::-1]) + combined_image_pil.save(result2Path) # 输出结果图2 + resResult = { + "hasError": False, + "num_follicle_groups": num_follicle_groups, + "num_big_follicles": num_big_follicles, + "num_small_follicles": num_small_follicles, + "originalImgPath": originalImgPath, + "result1Path": result1Path, + "result2Path": result2Path, + } + return resResult + + +# 检测结果返回 +@app.route("/api/checkResult", methods=["GET"]) +def checkResult(): + global resResult + return resResult + + +# 图片查询 +@app.route("/api/getPng/", methods=["GET"]) +def getPng(pngPath): + # 打开或处理图像 + img = Image.open("images/" + pngPath) + # 对图像进行处理，例如调整大小 + img = img.resize((800, 600)) + # 创建一个 BytesIO 对象来保存图像数据 + img_byte_arr = BytesIO() + img.save(img_byte_arr, format="PNG") + img_byte_arr.seek(0) + + # 使用 send_file 返回图像数据 + # return send_file(img_byte_arr, mimetype='image/jpeg') + + # 或者使用 make_response 来创建一个响应对象 + response = make_response(img_byte_arr.getvalue()) + response.headers.set("Content-Type", "image/jpeg") + response.headers.set("Content-Disposition", "attachment", filename=pngPath) + + return response + + +if __name__ == "__main__": + app.run(host="127.0.0.1", port=8006, debug=True) diff --git a/results_1.jpg b/results_1.jpg deleted file mode 100644 index 1350b09..0000000 Binary files a/results_1.jpg and /dev/null differ diff --git a/results_2.jpg b/results_2.jpg deleted file mode 100644 index 9c88351..0000000 Binary files a/results_2.jpg and /dev/null differ