upload

.firebase/hosting.cHVibGlj.cache

@@ -0,0 +1,2 @@
+index.html,1741591499789,a164687b08f5e91f6befe297edcde59d6005c1d8ff9a124bba47226efd0adf1c
+404.html,1741591499640,762bf484ba67404bd1a3b181546ea28d60dfddf18e9dd4795d8d25bcf3c1a890

.firebaserc

@@ -0,0 +1,5 @@
+{
+  "projects": {
+    "default": "skincancerscreening-a9c4d"
+  }
+}

.gcloudignore

@@ -0,0 +1,17 @@
+# This file specifies files that are *not* uploaded to Google Cloud
+# using gcloud. It follows the same syntax as .gitignore, with the addition of
+# "#!include" directives (which insert the entries of the given .gitignore-style
+# file at that point).
+#
+# For more information, run:
+#   $ gcloud topic gcloudignore
+#
+.gcloudignore
+# If you would like to upload your .git directory, .gitignore file or files
+# from your .gitignore file, remove the corresponding line
+# below:
+.git
+.gitignore
+
+node_modules
+#!include:.gitignore

firebase-debug.log

@@ -0,0 +1,90 @@
+[debug] [2025-03-10T08:17:30.321Z] ----------------------------------------------------------------------
+[debug] [2025-03-10T08:17:30.325Z] Command:       C:\Program Files\nodejs\node.exe C:\Users\phaml\AppData\Roaming\npm\node_modules\firebase-tools\lib\bin\firebase.js serve --only hosting
+[debug] [2025-03-10T08:17:30.325Z] CLI Version:   13.33.0
+[debug] [2025-03-10T08:17:30.325Z] Platform:      win32
+[debug] [2025-03-10T08:17:30.326Z] Node Version:  v20.17.0
+[debug] [2025-03-10T08:17:30.326Z] Time:          Mon Mar 10 2025 15:17:30 GMT+0700 (Indochina Time)
+[debug] [2025-03-10T08:17:30.326Z] ----------------------------------------------------------------------
+[debug] 
+[debug] [2025-03-10T08:17:30.987Z] > command requires scopes: ["email","openid","https://www.googleapis.com/auth/cloudplatformprojects.readonly","https://www.googleapis.com/auth/firebase","https://www.googleapis.com/auth/cloud-platform"]
+[debug] [2025-03-10T08:17:30.987Z] > authorizing via signed-in user (phamlethanhnhan0707@gmail.com)
+[debug] [2025-03-10T08:17:30.987Z] [iam] checking project skincancerscreening-a9c4d for permissions ["firebase.projects.get"]
+[debug] [2025-03-10T08:17:30.989Z] Checked if tokens are valid: false, expires at: 1741594954977
+[debug] [2025-03-10T08:17:30.989Z] Checked if tokens are valid: false, expires at: 1741594954977
+[debug] [2025-03-10T08:17:30.989Z] > refreshing access token with scopes: []
+[debug] [2025-03-10T08:17:30.992Z] >>> [apiv2][query] POST https://www.googleapis.com/oauth2/v3/token [none]
+[debug] [2025-03-10T08:17:30.992Z] >>> [apiv2][body] POST https://www.googleapis.com/oauth2/v3/token [omitted]
+[debug] [2025-03-10T08:17:31.169Z] <<< [apiv2][status] POST https://www.googleapis.com/oauth2/v3/token 200
+[debug] [2025-03-10T08:17:31.170Z] <<< [apiv2][body] POST https://www.googleapis.com/oauth2/v3/token [omitted]
+[debug] [2025-03-10T08:17:31.222Z] >>> [apiv2][query] POST https://cloudresourcemanager.googleapis.com/v1/projects/skincancerscreening-a9c4d:testIamPermissions [none]
+[debug] [2025-03-10T08:17:31.222Z] >>> [apiv2][(partial)header] POST https://cloudresourcemanager.googleapis.com/v1/projects/skincancerscreening-a9c4d:testIamPermissions x-goog-quota-user=projects/skincancerscreening-a9c4d
+[debug] [2025-03-10T08:17:31.223Z] >>> [apiv2][body] POST https://cloudresourcemanager.googleapis.com/v1/projects/skincancerscreening-a9c4d:testIamPermissions {"permissions":["firebase.projects.get"]}
+[debug] [2025-03-10T08:17:32.345Z] <<< [apiv2][status] POST https://cloudresourcemanager.googleapis.com/v1/projects/skincancerscreening-a9c4d:testIamPermissions 200
+[debug] [2025-03-10T08:17:32.346Z] <<< [apiv2][body] POST https://cloudresourcemanager.googleapis.com/v1/projects/skincancerscreening-a9c4d:testIamPermissions {"permissions":["firebase.projects.get"]}
+[debug] [2025-03-10T08:17:32.347Z] Checked if tokens are valid: true, expires at: 1741598250170
+[debug] [2025-03-10T08:17:32.347Z] Checked if tokens are valid: true, expires at: 1741598250170
+[debug] [2025-03-10T08:17:32.347Z] >>> [apiv2][query] GET https://cloudresourcemanager.googleapis.com/v1/projects/skincancerscreening-a9c4d [none]
+[debug] [2025-03-10T08:17:32.609Z] <<< [apiv2][status] GET https://cloudresourcemanager.googleapis.com/v1/projects/skincancerscreening-a9c4d 200
+[debug] [2025-03-10T08:17:32.609Z] <<< [apiv2][body] GET https://cloudresourcemanager.googleapis.com/v1/projects/skincancerscreening-a9c4d {"projectNumber":"830343088745","projectId":"skincancerscreening-a9c4d","lifecycleState":"ACTIVE","name":"skincancerscreening","labels":{"firebase":"enabled","firebase-core":"disabled"},"createTime":"2025-03-10T07:20:38.909685Z"}
+[debug] [2025-03-10T08:17:32.612Z] Checked if tokens are valid: true, expires at: 1741598250170
+[debug] [2025-03-10T08:17:32.612Z] Checked if tokens are valid: true, expires at: 1741598250170
+[debug] [2025-03-10T08:17:32.613Z] >>> [apiv2][query] GET https://firebasehosting.googleapis.com/v1beta1/projects/skincancerscreening-a9c4d/sites 
+[debug] [2025-03-10T08:17:33.344Z] <<< [apiv2][status] GET https://firebasehosting.googleapis.com/v1beta1/projects/skincancerscreening-a9c4d/sites 200
+[debug] [2025-03-10T08:17:33.345Z] <<< [apiv2][body] GET https://firebasehosting.googleapis.com/v1beta1/projects/skincancerscreening-a9c4d/sites {"sites":[{"name":"projects/skincancerscreening-a9c4d/sites/skincancerscreening-a9c4d","defaultUrl":"https://skincancerscreening-a9c4d.web.app","type":"DEFAULT_SITE"}]}
+[debug] [2025-03-10T08:17:33.345Z] Checked if tokens are valid: true, expires at: 1741598250170
+[debug] [2025-03-10T08:17:33.346Z] Checked if tokens are valid: true, expires at: 1741598250170
+[debug] [2025-03-10T08:17:33.346Z] >>> [apiv2][query] GET https://firebase.googleapis.com/v1beta1/projects/skincancerscreening-a9c4d/webApps/-/config [none]
+[debug] [2025-03-10T08:17:33.869Z] <<< [apiv2][status] GET https://firebase.googleapis.com/v1beta1/projects/skincancerscreening-a9c4d/webApps/-/config 200
+[debug] [2025-03-10T08:17:33.869Z] <<< [apiv2][body] GET https://firebase.googleapis.com/v1beta1/projects/skincancerscreening-a9c4d/webApps/-/config {"projectId":"skincancerscreening-a9c4d","storageBucket":"skincancerscreening-a9c4d.firebasestorage.app","apiKey":"AIzaSyBmT9PuKj5MnWE5mD1ivG4e09ENfb_ZObM","authDomain":"skincancerscreening-a9c4d.firebaseapp.com","messagingSenderId":"830343088745"}
+[debug] [2025-03-10T08:17:33.909Z] Checked if tokens are valid: true, expires at: 1741598250170
+[debug] [2025-03-10T08:17:33.909Z] Checked if tokens are valid: true, expires at: 1741598250170
+[debug] [2025-03-10T08:17:33.910Z] >>> [apiv2][query] GET https://firebase.googleapis.com/v1beta1/projects/skincancerscreening-a9c4d [none]
+[debug] [2025-03-10T08:17:35.294Z] <<< [apiv2][status] GET https://firebase.googleapis.com/v1beta1/projects/skincancerscreening-a9c4d 200
+[debug] [2025-03-10T08:17:35.294Z] <<< [apiv2][body] GET https://firebase.googleapis.com/v1beta1/projects/skincancerscreening-a9c4d {"projectId":"skincancerscreening-a9c4d","projectNumber":"830343088745","displayName":"skincancerscreening","name":"projects/skincancerscreening-a9c4d","resources":{"hostingSite":"skincancerscreening-a9c4d"},"state":"ACTIVE","etag":"1_b7dc9c78-635e-464c-a390-955983ce6ca1"}
+[info] i  hosting[skincancerscreening-a9c4d]: Serving hosting files from: public {"metadata":{"emulator":{"name":"hosting"},"message":"Serving hosting files from: \u001b[1mpublic\u001b[22m"}}
+[info] +  hosting[skincancerscreening-a9c4d]: Local server: http://localhost:5000 {"metadata":{"emulator":{"name":"hosting"},"message":"Local server: \u001b[4m\u001b[1mhttp://localhost:5000\u001b[22m\u001b[24m"}}
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET / HTTP/1.1" 200 - "-" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET / HTTP/1.1\" 200 - \"-\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[debug] [2025-03-10T08:18:29.064Z] >>> [apiv2][query] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-app-compat.js [none]
+[debug] [2025-03-10T08:18:29.073Z] >>> [apiv2][query] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-auth-compat.js [none]
+[debug] [2025-03-10T08:18:29.148Z] >>> [apiv2][query] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-database-compat.js [none]
+[debug] [2025-03-10T08:18:29.155Z] >>> [apiv2][query] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-firestore-compat.js [none]
+[debug] [2025-03-10T08:18:29.161Z] >>> [apiv2][query] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-functions-compat.js [none]
+[debug] [2025-03-10T08:18:29.166Z] >>> [apiv2][query] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-messaging-compat.js [none]
+[debug] [2025-03-10T08:18:29.244Z] <<< [apiv2][status] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-app-compat.js 200
+[debug] [2025-03-10T08:18:29.244Z] <<< [apiv2][body] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-app-compat.js [stream]
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET /__/firebase/11.4.0/firebase-app-compat.js HTTP/1.1" 200 10177 "http://localhost:5000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET /__/firebase/11.4.0/firebase-app-compat.js HTTP/1.1\" 200 10177 \"http://localhost:5000/\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[debug] [2025-03-10T08:18:29.261Z] <<< [apiv2][status] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-auth-compat.js 200
+[debug] [2025-03-10T08:18:29.261Z] <<< [apiv2][body] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-auth-compat.js [stream]
+[debug] [2025-03-10T08:18:29.267Z] >>> [apiv2][query] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-storage-compat.js [none]
+[debug] [2025-03-10T08:18:29.287Z] <<< [apiv2][status] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-database-compat.js 200
+[debug] [2025-03-10T08:18:29.287Z] <<< [apiv2][body] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-database-compat.js [stream]
+[debug] [2025-03-10T08:18:29.293Z] <<< [apiv2][status] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-messaging-compat.js 200
+[debug] [2025-03-10T08:18:29.293Z] <<< [apiv2][body] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-messaging-compat.js [stream]
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET /__/firebase/11.4.0/firebase-messaging-compat.js HTTP/1.1" 200 9968 "http://localhost:5000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET /__/firebase/11.4.0/firebase-messaging-compat.js HTTP/1.1\" 200 9968 \"http://localhost:5000/\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[debug] [2025-03-10T08:18:29.303Z] >>> [apiv2][query] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-analytics-compat.js [none]
+[debug] [2025-03-10T08:18:29.304Z] <<< [apiv2][status] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-functions-compat.js 200
+[debug] [2025-03-10T08:18:29.304Z] <<< [apiv2][body] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-functions-compat.js [stream]
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET /__/firebase/11.4.0/firebase-functions-compat.js HTTP/1.1" 200 3974 "http://localhost:5000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET /__/firebase/11.4.0/firebase-functions-compat.js HTTP/1.1\" 200 3974 \"http://localhost:5000/\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET /__/firebase/11.4.0/firebase-auth-compat.js HTTP/1.1" 200 40259 "http://localhost:5000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET /__/firebase/11.4.0/firebase-auth-compat.js HTTP/1.1\" 200 40259 \"http://localhost:5000/\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[debug] [2025-03-10T08:18:29.311Z] <<< [apiv2][status] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-storage-compat.js 200
+[debug] [2025-03-10T08:18:29.311Z] <<< [apiv2][body] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-storage-compat.js [stream]
+[debug] [2025-03-10T08:18:29.315Z] >>> [apiv2][query] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-remote-config-compat.js [none]
+[debug] [2025-03-10T08:18:29.319Z] >>> [apiv2][query] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-performance-compat.js [none]
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET /__/firebase/11.4.0/firebase-storage-compat.js HTTP/1.1" 200 13023 "http://localhost:5000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET /__/firebase/11.4.0/firebase-storage-compat.js HTTP/1.1\" 200 13023 \"http://localhost:5000/\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[debug] [2025-03-10T08:18:29.324Z] <<< [apiv2][status] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-firestore-compat.js 200
+[debug] [2025-03-10T08:18:29.324Z] <<< [apiv2][body] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-firestore-compat.js [stream]
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET /__/firebase/init.js?useEmulator=true HTTP/1.1" 200 - "http://localhost:5000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET /__/firebase/init.js?useEmulator=true HTTP/1.1\" 200 - \"http://localhost:5000/\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[debug] [2025-03-10T08:18:29.340Z] <<< [apiv2][status] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-analytics-compat.js 200
+[debug] [2025-03-10T08:18:29.340Z] <<< [apiv2][body] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-analytics-compat.js [stream]
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET /__/firebase/11.4.0/firebase-analytics-compat.js HTTP/1.1" 200 9132 "http://localhost:5000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET /__/firebase/11.4.0/firebase-analytics-compat.js HTTP/1.1\" 200 9132 \"http://localhost:5000/\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET /__/firebase/11.4.0/firebase-database-compat.js HTTP/1.1" 200 48150 "http://localhost:5000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET /__/firebase/11.4.0/firebase-database-compat.js HTTP/1.1\" 200 48150 \"http://localhost:5000/\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[debug] [2025-03-10T08:18:29.359Z] <<< [apiv2][status] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-remote-config-compat.js 200
+[debug] [2025-03-10T08:18:29.359Z] <<< [apiv2][body] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-remote-config-compat.js [stream]
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET /__/firebase/11.4.0/firebase-remote-config-compat.js HTTP/1.1" 200 9172 "http://localhost:5000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET /__/firebase/11.4.0/firebase-remote-config-compat.js HTTP/1.1\" 200 9172 \"http://localhost:5000/\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[debug] [2025-03-10T08:18:29.366Z] <<< [apiv2][status] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-performance-compat.js 200
+[debug] [2025-03-10T08:18:29.366Z] <<< [apiv2][body] GET https://www.gstatic.com/firebasejs/11.4.0/firebase-performance-compat.js [stream]
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET /__/firebase/11.4.0/firebase-performance-compat.js HTTP/1.1" 200 13495 "http://localhost:5000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET /__/firebase/11.4.0/firebase-performance-compat.js HTTP/1.1\" 200 13495 \"http://localhost:5000/\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET /__/firebase/11.4.0/firebase-firestore-compat.js HTTP/1.1" 200 102688 "http://localhost:5000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET /__/firebase/11.4.0/firebase-firestore-compat.js HTTP/1.1\" 200 102688 \"http://localhost:5000/\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[info] i  hosting: ::1 - - [10/Mar/2025:08:18:29 +0000] "GET /favicon.ico HTTP/1.1" 404 - "http://localhost:5000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:18:29 +0000] \"GET /favicon.ico HTTP/1.1\" 404 - \"http://localhost:5000/\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[info] i  hosting: ::1 - - [10/Mar/2025:08:22:07 +0000] "GET / HTTP/1.1" 200 - "-" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:22:07 +0000] \"GET / HTTP/1.1\" 200 - \"-\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}
+[info] i  hosting: ::1 - - [10/Mar/2025:08:25:59 +0000] "GET / HTTP/1.1" 200 - "-" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36" {"metadata":{"emulator":{"name":"hosting"},"message":"::1 - - [10/Mar/2025:08:25:59 +0000] \"GET / HTTP/1.1\" 200 - \"-\" \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36\""}}

firebase.json

@@ -0,0 +1,10 @@
+{
+  "hosting": {
+    "public": "public",
+    "ignore": [
+      "firebase.json",
+      "**/.*",
+      "**/node_modules/**"
+    ]
+  }
+}

main.py

@@ -0,0 +1,278 @@
+import os
+import io
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from torchvision import transforms, models
+from PIL import Image
+import cv2
+import numpy as np
+from flask import jsonify, request
+import functions_framework
+
+# Set device (Cloud Functions generally use CPU, but GPU will be used if available)
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+
+###############################################################################
+# Utility Functions for Image Preprocessing (Optional)
+###############################################################################
+def remove_hair_and_markings(img_bgr, kernel_size=17):
+    """Remove thin hair and markings using morphological operations."""
+    gray = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2GRAY)
+    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (kernel_size, kernel_size))
+    blackhat = cv2.morphologyEx(gray, cv2.MORPH_BLACKHAT, kernel)
+    _, mask = cv2.threshold(blackhat, 10, 255, cv2.THRESH_BINARY)
+    inpainted = cv2.inpaint(img_bgr, mask, 3, cv2.INPAINT_TELEA)
+    return inpainted
+
+def normalize_color(img_bgr):
+    """Per-channel normalization: subtract mean and divide by std for each channel."""
+    img_float = img_bgr.astype(np.float32)
+    b, g, r = cv2.split(img_float)
+    for channel in (b, g, r):
+        mean_val = np.mean(channel)
+        std_val  = np.std(channel) + 1e-8
+        channel[:] = (channel - mean_val) / std_val
+    normalized = cv2.merge([b, g, r])
+    return normalized
+
+def mmwf_filter(gray_image, window_size=3, noise_variance=0.01):
+    """Apply the Median–Modified Wiener Filter (MMWF) on a grayscale image."""
+    if gray_image.dtype != np.float32:
+        gray_image = gray_image.astype(np.float32)
+    pad_size = window_size // 2
+    padded = np.pad(gray_image, pad_size, mode='reflect')
+    filtered = np.zeros_like(gray_image, dtype=np.float32)
+    rows, cols = gray_image.shape
+    for i in range(rows):
+        for j in range(cols):
+            local_patch = padded[i:i+window_size, j:j+window_size]
+            mu_m = np.median(local_patch)
+            sigma_sq = local_patch.var()
+            a_val = gray_image[i, j]
+            if sigma_sq < 1e-12:
+                filtered[i, j] = mu_m
+            else:
+                filtered[i, j] = mu_m + ((sigma_sq - noise_variance) / sigma_sq) * (a_val - mu_m)
+    return filtered
+
+def mmwf_filter_color(img_bgr, window_size=3, noise_variance=0.01):
+    """Apply MMWF to each channel of a BGR image."""
+    if img_bgr.dtype != np.float32:
+        img_bgr = img_bgr.astype(np.float32)
+    b, g, r = cv2.split(img_bgr)
+    b_denoised = mmwf_filter(b, window_size, noise_variance)
+    g_denoised = mmwf_filter(g, window_size, noise_variance)
+    r_denoised = mmwf_filter(r, window_size, noise_variance)
+    denoised_bgr = cv2.merge([b_denoised, g_denoised, r_denoised])
+    return denoised_bgr
+
+def preprocess_image(image):
+    """
+    Optionally, apply preprocessing steps:
+      1. Convert from PIL RGB to NumPy BGR.
+      2. Remove hair/markings.
+      3. Normalize color.
+      4. Apply MMWF filter.
+      5. Convert back to PIL RGB.
+    """
+    image_np = np.array(image)
+    image_bgr = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)
+    image_bgr = remove_hair_and_markings(image_bgr, kernel_size=17)
+    image_bgr = normalize_color(image_bgr)
+    image_bgr = cv2.normalize(image_bgr, None, alpha=0, beta=255, norm_type=cv2.NORM_MINMAX).astype(np.uint8)
+    # image_bgr = mmwf_filter_color(image_bgr, window_size=3, noise_variance=0.01)
+    image_rgb = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2RGB)
+    return Image.fromarray(image_rgb)
+
+###############################################################################
+# Helper Modules for the Classifier
+###############################################################################
+def create_classification_head(input_dim, num_classes):
+    return nn.Sequential(
+        nn.Linear(input_dim, 512),
+        nn.ReLU(),
+        nn.Dropout(0.5),
+        nn.Linear(512, num_classes)
+    )
+
+class MetadataEncoder(nn.Module):
+    def __init__(self, input_size, output_size):
+        super(MetadataEncoder, self).__init__()
+        self.encoder = nn.Sequential(
+            nn.Conv1d(1, 16, kernel_size=3, padding=1),
+            nn.BatchNorm1d(16),
+            nn.ReLU(),
+            nn.Conv1d(16, 32, kernel_size=3, padding=1),
+            nn.BatchNorm1d(32),
+            nn.ReLU(),
+            nn.Flatten(),
+            nn.Linear(32 * input_size, output_size),
+            nn.ReLU()
+        )
+    def forward(self, x):
+        x = x.unsqueeze(1)
+        return self.encoder(x)
+
+class GraphAttentionLayer(nn.Module):
+    def __init__(self, in_features, out_features, dropout=0.0, alpha=0.2):
+        super(GraphAttentionLayer, self).__init__()
+        self.W = nn.Linear(in_features, out_features, bias=False)
+        self.a = nn.Parameter(torch.empty(2 * out_features, 1))
+        nn.init.xavier_uniform_(self.W.weight.data, gain=1.414)
+        nn.init.xavier_uniform_(self.a.data, gain=1.414)
+        self.leakyrelu = nn.LeakyReLU(alpha)
+        self.dropout = nn.Dropout(dropout)
+    def forward(self, h, adj=None):
+        Wh = self.W(h)
+        batch_size, N, _ = Wh.size()
+        Wh_i = Wh.unsqueeze(2).repeat(1, 1, N, 1)
+        Wh_j = Wh.unsqueeze(1).repeat(1, N, 1, 1)
+        e = self.leakyrelu(torch.matmul(torch.cat([Wh_i, Wh_j], dim=-1), self.a).squeeze(-1))
+        attention = F.softmax(e, dim=-1)
+        attention = self.dropout(attention)
+        h_prime = torch.matmul(attention, Wh)
+        return h_prime, attention
+
+class MultiHeadGraphAttentionLayer(nn.Module):
+    def __init__(self, in_features, out_features, num_heads=4, dropout=0.0, alpha=0.2):
+        super(MultiHeadGraphAttentionLayer, self).__init__()
+        self.num_heads = num_heads
+        self.heads = nn.ModuleList([
+            GraphAttentionLayer(in_features, out_features, dropout, alpha)
+            for _ in range(num_heads)
+        ])
+        self.linear = nn.Linear(num_heads * out_features, out_features)
+    def forward(self, h):
+        head_outputs = [head(h)[0] for head in self.heads]
+        h_concat = torch.cat(head_outputs, dim=-1)
+        return self.linear(h_concat)
+
+class EnhancedGraphFusion(nn.Module):
+    def __init__(self, in_features, out_features, num_heads=4, num_layers=2, dropout=0.0, alpha=0.2):
+        super(EnhancedGraphFusion, self).__init__()
+        self.global_init = nn.Parameter(torch.zeros(in_features))
+        self.layers = nn.ModuleList([
+            MultiHeadGraphAttentionLayer(in_features, in_features, num_heads, dropout, alpha)
+            for _ in range(num_layers)
+        ])
+        self.norm = nn.LayerNorm(in_features)
+        self.proj = nn.Linear(in_features, out_features)
+    def forward(self, image_nodes, metadata_feat):
+        batch_size = image_nodes.size(0)
+        metadata_node = metadata_feat.unsqueeze(1)
+        global_node = self.global_init.unsqueeze(0).expand(batch_size, -1).unsqueeze(1)
+        h = torch.cat([image_nodes, metadata_node, global_node], dim=1)
+        for layer in self.layers:
+            residual = h
+            h = layer(h)
+            h = F.elu(h)
+            h = self.norm(h + residual)
+        fused = h[:, -1, :]
+        return self.proj(fused)
+
+###############################################################################
+# DenseNet201-based Classifier for Skin Lesion Classification
+###############################################################################
+class DenseNet201Classifier(nn.Module):
+    def __init__(self, num_classes=6, metadata_input_size=3, metadata_output_size=768):
+        super(DenseNet201Classifier, self).__init__()
+        self.densenet = models.densenet201(pretrained=True)
+        self.num_features = self.densenet.classifier.in_features
+        self.img_proj = nn.Linear(self.num_features, metadata_output_size)
+        self.metadata_encoder = MetadataEncoder(metadata_input_size, metadata_output_size)
+        self.enhanced_graph_fusion = EnhancedGraphFusion(
+            in_features=metadata_output_size,
+            out_features=metadata_output_size,
+            num_heads=4,
+            num_layers=2,
+            dropout=0.1,
+            alpha=0.2
+        )
+        self.head = create_classification_head(metadata_output_size, num_classes)
+    def forward_feature_map(self, x):
+        features = self.densenet.features(x)
+        return F.relu(features, inplace=True)
+    def forward(self, x, metadata):
+        fmap = self.forward_feature_map(x)
+        batch_size, C, H, W = fmap.shape
+        image_nodes = fmap.view(batch_size, C, H * W).transpose(1, 2)
+        image_nodes = self.img_proj(image_nodes)
+        metadata_features = self.metadata_encoder(metadata)
+        fused_features = self.enhanced_graph_fusion(image_nodes, metadata_features)
+        return self.head(fused_features)
+
+###############################################################################
+# Inference Pipeline Setup
+###############################################################################
+# Define image transformation for inference
+transform = transforms.Compose([
+    transforms.Resize((224, 224)),
+    transforms.ToTensor(),
+    transforms.Normalize(mean=[0.485, 0.456, 0.406],
+                         std=[0.229, 0.224, 0.225])
+])
+
+def load_model(model_path='pd4_model.pth'):
+    """Load the pre-trained DenseNet201Classifier model."""
+    num_classes = 6
+    metadata_input_size = 3  # Expecting: age, gender, skin_cancer_history
+    model = DenseNet201Classifier(num_classes=num_classes,
+                                  metadata_input_size=metadata_input_size,
+                                  metadata_output_size=768)
+    state_dict = torch.load(model_path, map_location='cpu')
+    model.load_state_dict(state_dict)
+    model.to(device)
+    model.eval()
+    return model
+
+# Load the model once at function startup
+model = load_model()
+
+###############################################################################
+# Cloud Function HTTP Endpoint (Using functions_framework)
+###############################################################################
+@functions_framework.http
+def predict(request):
+    """
+    HTTP-triggered Cloud Function that accepts a POST request with an image file.
+    Optionally, you can uncomment the preprocessing step if needed.
+    Returns the predicted class and confidence as JSON.
+    """
+    if request.method != 'POST':
+        return jsonify({'error': 'Only POST method is supported.'}), 405
+
+    if 'file' not in request.files:
+        return jsonify({'error': 'No file provided.'}), 400
+
+    file = request.files['file']
+    try:
+        image = Image.open(file.stream).convert('RGB')
+    except Exception as e:
+        return jsonify({'error': 'Invalid image file.'}), 400
+
+    # Optionally apply advanced preprocessing:
+    image = preprocess_image(image)
+    
+    image_tensor = transform(image).unsqueeze(0).to(device)
+    # Use default metadata values (e.g., zeros for [age, gender, skin_cancer_history])
+    default_metadata = torch.zeros((1, 3), dtype=torch.float).to(device)
+
+    with torch.no_grad():
+        outputs = model(image_tensor, default_metadata)
+        probabilities = F.softmax(outputs, dim=1)
+        confidence, predicted = torch.max(probabilities, dim=1)
+
+    result = {
+        'predicted_class': predicted.item(),
+        'confidence': confidence.item()
+    }
+    return jsonify(result)
+
+if __name__ == '__main__':
+    import os
+    port = int(os.environ.get("PORT", 8080))
+    # The functions_framework creates a Flask app that exposes your target function.
+    from functions_framework import create_app
+    app = create_app(target="predict")
+    app.run(host="0.0.0.0", port=port, debug=True)

package-lock.json

@@ -0,0 +1,6 @@
+{
+  "name": "skincancerscreening",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {}
+}

pd4_model.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cd2aacb12d67299548ad2905a9f11f7bf4ae1d1a4a41b37aa06169a1e9f8820c
+size 129438302

public/404.html

@@ -0,0 +1,33 @@
+<!DOCTYPE html>
+<html>
+  <head>
+    <meta charset="utf-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1">
+    <title>Page Not Found</title>
+
+    <style media="screen">
+      body { background: #ECEFF1; color: rgba(0,0,0,0.87); font-family: Roboto, Helvetica, Arial, sans-serif; margin: 0; padding: 0; }
+      #message { background: white; max-width: 360px; margin: 100px auto 16px; padding: 32px 24px 16px; border-radius: 3px; }
+      #message h3 { color: #888; font-weight: normal; font-size: 16px; margin: 16px 0 12px; }
+      #message h2 { color: #ffa100; font-weight: bold; font-size: 16px; margin: 0 0 8px; }
+      #message h1 { font-size: 22px; font-weight: 300; color: rgba(0,0,0,0.6); margin: 0 0 16px;}
+      #message p { line-height: 140%; margin: 16px 0 24px; font-size: 14px; }
+      #message a { display: block; text-align: center; background: #039be5; text-transform: uppercase; text-decoration: none; color: white; padding: 16px; border-radius: 4px; }
+      #message, #message a { box-shadow: 0 1px 3px rgba(0,0,0,0.12), 0 1px 2px rgba(0,0,0,0.24); }
+      #load { color: rgba(0,0,0,0.4); text-align: center; font-size: 13px; }
+      @media (max-width: 600px) {
+        body, #message { margin-top: 0; background: white; box-shadow: none; }
+        body { border-top: 16px solid #ffa100; }
+      }
+    </style>
+  </head>
+  <body>
+    <div id="message">
+      <h2>404</h2>
+      <h1>Page Not Found</h1>
+      <p>The specified file was not found on this website. Please check the URL for mistakes and try again.</p>
+      <h3>Why am I seeing this?</h3>
+      <p>This page was generated by the Firebase Command-Line Interface. To modify it, edit the <code>404.html</code> file in your project's configured <code>public</code> directory.</p>
+    </div>
+  </body>
+</html>

public/index.html

@@ -0,0 +1,123 @@
+<!doctype html>
+<html>
+  <head>
+    <title>Skin Lesion Screening</title>
+    <meta name="viewport" content="width=device-width, initial-scale=1">
+    <style>
+      body {
+        font-family: Arial, sans-serif;
+        margin: 40px;
+        background-color: #f9f9f9;
+      }
+      .container {
+        max-width: 500px;
+        margin: auto;
+        background: #fff;
+        padding: 20px;
+        border-radius: 8px;
+        box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+        text-align: center;
+      }
+      input, select, button {
+        width: 100%;
+        padding: 10px;
+        margin: 10px 0;
+        font-size: 1em;
+      }
+      button {
+        background-color: #007BFF;
+        border: none;
+        color: white;
+        cursor: pointer;
+        border-radius: 4px;
+      }
+      button:hover {
+        background-color: #0056b3;
+      }
+      .result {
+        margin-top: 20px;
+        font-size: 1.2em;
+        color: #333;
+        white-space: pre-line;
+      }
+    </style>
+  </head>
+  <body>
+    <div class="container">
+      <h1>Skin Lesion Screening</h1>
+      <form id="upload-form">
+        <!-- Image File Input -->
+        <label for="file">Upload Image:</label>
+        <input type="file" id="file" accept="image/*" capture="camera" required>
+        
+        <!-- Metadata: Age -->
+        <label for="age">Age:</label>
+        <input type="number" id="age" placeholder="Enter your age" required>
+        
+        <!-- Metadata: Gender -->
+        <label for="gender">Gender:</label>
+        <select id="gender" required>
+          <option value="" disabled selected>Select your gender</option>
+          <option value="0">Male</option>
+          <option value="1">Female</option>
+          <option value="2">Other</option>
+        </select>
+        
+        <!-- Metadata: Skin Cancer History -->
+        <label for="cancerHistory">History of Skin Cancer:</label>
+        <select id="cancerHistory" required>
+          <option value="" disabled selected>Do you have a history of skin cancer?</option>
+          <option value="0">No</option>
+          <option value="1">Yes</option>
+        </select>
+        
+        <button type="submit">Analyze</button>
+      </form>
+      <div id="result" class="result"></div>
+    </div>
+    <script>
+      document.getElementById('upload-form').addEventListener('submit', async function(e) {
+        e.preventDefault();
+        
+        // Get the inputs
+        const fileInput = document.getElementById('file');
+        const ageInput = document.getElementById('age');
+        const genderInput = document.getElementById('gender');
+        const cancerHistoryInput = document.getElementById('cancerHistory');
+        
+        if (!fileInput.files.length) {
+          alert("Please select an image file.");
+          return;
+        }
+        
+        // Create a FormData object and append file and metadata
+        const formData = new FormData();
+        formData.append('file', fileInput.files[0]);
+        formData.append('age', ageInput.value);
+        formData.append('gender', genderInput.value);
+        formData.append('cancer_history', cancerHistoryInput.value);
+        
+        // Replace this URL with your actual Cloud Function endpoint URL
+        const functionUrl = 'https://us-central1-skincancerscreening.cloudfunctions.net/predict';
+        
+        // Send POST request to the backend
+        try {
+          const response = await fetch(functionUrl, {
+            method: 'POST',
+            body: formData
+          });
+          
+          if (!response.ok) {
+            throw new Error("Network response was not ok");
+          }
+          
+          const data = await response.json();
+          document.getElementById('result').innerText =
+            'Predicted Class: ' + data.predicted_class + '\nConfidence: ' + (data.confidence * 100).toFixed(2) + '%';
+        } catch (error) {
+          document.getElementById('result').innerText = 'Error: ' + error;
+        }
+      });
+    </script>
+  </body>
+</html>

requirements.txt

@@ -0,0 +1,5 @@
+functions-framework==3.1.0
+torch==1.13.1
+torchvision==0.14.1
+Pillow==9.4.0
+opencv-python-headless==4.7.0.72