update web page

.gitignore

@@ -8,4 +8,6 @@ nlp/__pycache__/
 __pycache__/
 pyWeb/
 research/imgcensor/model/
-cv/model/
+cv/model/
+cv/static/ImgCensorUpload/
+cv/static/SkinUpload/

cv/controllers.py

@@ -206,8 +206,73 @@ def infer_from_img(self, img):
         }
 
 
+class NSFWEstimator:
+    """
+    NSFW Estimator Class Wrapper
+    """
+
+    def __init__(self, pretrained_model_path="cv/model/DenseNet121_NSFW.pth", num_cls=5):
+        self.num_cls = num_cls
+        model = models.densenet121(pretrained=True)
+        num_ftrs = model.classifier.in_features
+        model.classifier = nn.Linear(num_ftrs, self.num_cls)
+
+        device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
+
+        model.load_state_dict(torch.load(pretrained_model_path))
+
+        model.to(device)
+        model.eval()
+
+        self.device = device
+        self.model = model
+        self.topK = 5
+        self.mapping = {
+            0: 'drawings',
+            1: 'hentai',
+            2: 'neutral',
+            3: 'porn',
+            4: 'sexy'
+        }
+
+    def infer(self, img_file):
+        img = Image.open(img_file)
+
+        preprocess = transforms.Compose([
+            transforms.Resize(224),
+            transforms.CenterCrop(224),
+            transforms.ToTensor(),
+            transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+        ])
+
+        img = preprocess(img)
+        img.unsqueeze_(0)
+
+        img = img.to(self.device)
+
+        outputs = self.model(img)
+        outputs = F.softmax(outputs, dim=1)
+
+        topK_prob, topK_label = torch.topk(outputs, self.topK)
+        prob = topK_prob.to("cpu").detach().numpy().tolist()
+
+        _, predicted = torch.max(outputs.data, 1)
+
+        return {
+            "status": 0,
+            "message": "success",
+            "results": [
+                {
+                    "prob": round(prob[0][i], 4),
+                    "type": self.mapping[int(topK_label[0][i].to("cpu"))],
+                } for i in range(self.topK)
+            ]
+        }
+
+
 beauty_recognizer = BeautyRecognizer()
 skin_disease_recognizer = SkinDiseaseRecognizer(num_cls=198)
+nsfw_estimator = NSFWEstimator(num_cls=5)
 
 
 def upload_and_rec_beauty(request):
@@ -334,3 +399,55 @@ def upload_and_rec_skin_disease(request):
         json_result = json.dumps(result, ensure_ascii=False)
 
         return HttpResponse(json_result)
+
+
+def upload_and_rec_porn(request):
+    """
+    upload and recognize porn image
+    :param request:
+    :return:
+    """
+    image_dir = 'cv/static/ImgCensorUpload'
+    if not os.path.exists(image_dir):
+        os.makedirs(image_dir)
+
+    result = {}
+
+    if request.method == "POST":
+        image = request.FILES.get("image", None)
+        if not image:
+            result['code'] = 3
+            result['msg'] = 'Invalid Path for Image'
+            result['results'] = None
+
+            json_result = json.dumps(result, ensure_ascii=False)
+
+            return HttpResponse(json_result)
+        else:
+            destination = open(os.path.join(image_dir, image.name), 'wb+')
+            for chunk in image.chunks():
+                destination.write(chunk)
+            destination.close()
+
+            tik = time.time()
+            imagepath = URL_PORT + '/static/ImgCensorUpload/' + image.name
+
+            nswf_result = nsfw_estimator.infer(os.path.join(image_dir, image.name))
+
+            result['code'] = 0
+            result['msg'] = 'success'
+            result['imgpath'] = imagepath
+            result['results'] = nswf_result['results']
+            result['elapse'] = round(time.time() - tik, 2)
+
+            json_str = json.dumps(result, ensure_ascii=False)
+
+            return HttpResponse(json_str)
+    else:
+        result['code'] = 3
+        result['msg'] = 'Invalid HTTP Method'
+        result['data'] = None
+
+        json_result = json.dumps(result, ensure_ascii=False)
+
+        return HttpResponse(json_result)

cv/templates/index.html

@@ -150,7 +150,7 @@ <h2>Research Achievements</h2>
                 <div class="row">
                     <div class="col-md-6">
                         <div class="portfolio-item">
-                            <a href="#">
+                            <a href="nsfwview" target="_blank">
                                 <img class="img-portfolio img-responsive"
                                      src="/static/img/portfolio-1.png">
                             </a>

cv/templates/mcloud.html

@@ -541,8 +541,9 @@ <h5>We're on social networks</h5>
             <div class="col-md-12">
                 <p>Copyright &copy; LucasX. All rights reserved.</p>
                 <div class="credits">
-                    Designed by LucasX.
+                    Designed by <a href="https://www.zhihu.com/people/xulu-0620">LucasX</a>.
                 </div>
+                <p>Powered by <a href="index">XCloud</a></p>
             </div>
         </div>
     </div>

cv/templates/nsfw.html

@@ -0,0 +1,71 @@
+<!DOCTYPE html>
+<html>
+<head>
+    <meta charset="UTF-8">
+    <title>Porn Image Recognition</title>
+    {#    {% load static %}#}
+    <script src="https://code.jquery.com/jquery-3.2.1.js"></script>
+    <link rel="stylesheet"
+          href="http://cdn.amazeui.org/amazeui/2.7.2/css/amazeui.min.css">
+    <link rel="icon" type="image/png" sizes="192x192" href="/static/favicon.ico">
+    <script src="http://cdn.amazeui.org/amazeui/2.7.2/js/amazeui.min.js"></script>
+    <script src="http://cdn.amazeui.org/amazeui/2.7.2/js/amazeui.ie8polyfill.min.js"></script>
+    <script src="http://cdn.amazeui.org/amazeui/2.7.2/js/amazeui.widgets.helper.min.js"></script>
+</head>
+<body>
+<h2 align="center">Porn Image Recognition</h2>
+<div align="center">
+    <form enctype="multipart/form-data">{% csrf_token %}
+        <div class="am-form-group am-form-file">
+            <button type="button" class="am-btn am-btn-danger am-btn-sm">
+                <i class="am-icon-cloud-upload"></i> Choose Image
+                <input type="file" placeholder="upload image" name="image">
+                {#                <input id="doc-form-file" type="file" multiple>#}
+            </button>
+        </div>
+        <input type="button" value="detect" id='upload-btn'
+               class="am-btn am-btn-success" onclick="upload()">
+    </form>
+    <img class="am-img-responsive" alt="" src="" style="max-height: 320px;
+    margin-top: 5px"/>
+</div>
+<div align="center">
+    <p>The image is <span id="desc" style="color:
+    red"></span>, AI takes
+        <span id="time" style="color: red">0</span> seconds!
+    </p>
+</div>
+
+<footer style="text-align: center">
+    Powered by <a href="http://www.lucasx.top:8001/cv/mcloud" target="_blank">MCloud</a>
+    Supported by <a href="https://www.zhihu.com/people/xulu-0620/activities"
+                    target="_blank">LucasX</a>
+</footer>
+
+<script>
+    function upload() {
+        var src = $("input[name='image']").val();
+        var imgName = src.split("\\")[src.split('\\').length - 1];
+        var data = new FormData($('form').get(0));
+
+        $.ajax({
+            url: 'nsfw',
+            type: 'POST',
+            data: data,
+            cache: false,
+            processData: false,
+            contentType: false,
+            success: function (data) {
+                console.log('success');
+                var result = eval('(' + data + ')');
+                $('#desc').text(result.results[0].type);
+                $('#time').text(result.elapse);
+                $('img').attr('src', '../../../static/ImgCensorUpload/' + imgName);
+            }
+        });
+
+        return false;
+    }
+</script>
+</body>
+</html>

cv/urls.py

@@ -11,6 +11,8 @@
     # path('sdr', views.sdr, name='sdr'),
     url('fbpview', views.fbp_view, name='fbpview'),
     url('fbp', views.fbp, name='fbp'),
+    url('nsfwview', views.nsfw_view, name='nsfwview'),
+    url('nsfw', views.nsfw, name='nsfw'),
     url('skinview', views.skin_view, name='skinview'),
     url('mcloud/skin', views.rec_skin, name='recskin'),
     url('detectface', views.detect_face, name='detectface'),

cv/views.py

@@ -41,6 +41,15 @@ def skin_view(request):
     return render(request, 'skin.html')
 
 
+def nsfw_view(request):
+    return render(request, 'nsfw.html')
+
+
+def nsfw(request):
+    from cv import controllers
+    return controllers.upload_and_rec_porn(request)
+
+
 def detect_face(request):
     """
     face detection