From ec64aca382c766f54e99b7486a8e90685ab5a2b6 Mon Sep 17 00:00:00 2001
From: Sachin Acharya
 <51048248+sachin-acharya-projects@users.noreply.github.com>
Date: Thu, 18 Jul 2024 18:36:14 +0545
Subject: [PATCH] Added verbose error message for prediction failure & added
 exception handling for FileNotFound exception in predict method.

---
 Backend/main.py                        | 21 +++++++++---
 Frontend/src/Components/UploadForm.tsx | 45 +++++++++++++++++++++++---
 2 files changed, 57 insertions(+), 9 deletions(-)

diff --git a/Backend/main.py b/Backend/main.py
index 4acec20b..f4cfe298 100644
--- a/Backend/main.py
+++ b/Backend/main.py
@@ -22,13 +22,16 @@ def predict_image(image_src: str, confidence: int = 0.5) -> str | None:
     Returns:
         str | None: Classname of the predicted image.
     """
-    results: Results = model(image_src)
-
+    try:
+        results: Results = model(image_src)
+    except FileNotFoundError:
+        return
+    
     for result in results:
         names = result.names
         probs = result.probs.data.tolist()
         max_prob_index = np.argmax(probs)
-        
+
         if probs[max_prob_index] < confidence:
             return None
         print(names[max_prob_index], type(names[max_prob_index]))
@@ -67,7 +70,7 @@ def predict():
             400,
         )
 
-    # print(file.mimetype)
+    print(file.mimetype)
     if file and "image" in file.mimetype.lower():
         filename = secure_filename(file.filename)
         filepath = os.path.join(app.config["UPLOAD_FOLDER"], filename)
@@ -92,7 +95,15 @@ def predict():
             try:
                 disease_data: Dict = json_data[disease_id]
             except KeyError:
-                return jsonify({"status": False, "message": "Disease Not Found in our database"}), 404
+                return (
+                    jsonify(
+                        {
+                            "status": False,
+                            "message": "Disease Not Found in our database",
+                        }
+                    ),
+                    404,
+                )
 
             return jsonify({"status": True, "data": disease_data}), 200
     return (
diff --git a/Frontend/src/Components/UploadForm.tsx b/Frontend/src/Components/UploadForm.tsx
index 33e84db6..223e28ce 100644
--- a/Frontend/src/Components/UploadForm.tsx
+++ b/Frontend/src/Components/UploadForm.tsx
@@ -51,7 +51,44 @@ export default function UploadForm({ image, onPress }: Props) {
                             "Cannot process your data due to some user-side errors."
                     )
                 else if (statusCode === 422)
-                    toast.error("Cannot predict the disease in the image.")
+                    toast.error(
+                        "Cannot predict the disease in the image. Please select another image.",
+                        {
+                            action: {
+                                label: "Why?",
+                                onClick: () => {
+                                    toast.error(
+                                        <div>
+                                            <p className="font-semibold text-[16px] mb-2">
+                                                Possible Reasons for Detection
+                                                Failure
+                                            </p>
+                                            <ol className="list-decimal list-inside pl-5 pr-5 flex flex-col gap-2">
+                                                <li>
+                                                    The image is <b>unclear</b>,
+                                                    making it difficult to
+                                                    accurately identify the
+                                                    disease.
+                                                </li>
+                                                <li>
+                                                    The image <b>size</b> is too{" "}
+                                                    <b>broad</b>. Please take a{" "}
+                                                    <b>close-up</b> picture of
+                                                    the <b>plant leaf</b> for
+                                                    better results.
+                                                </li>
+                                                <li>
+                                                    The disease is{" "}
+                                                    <b>not registered</b> in our
+                                                    database.
+                                                </li>
+                                            </ol>
+                                        </div>
+                                    )
+                                },
+                            },
+                        }
+                    )
             } else if (error instanceof Error) console.error(error.message)
             else console.error(error)
         },
@@ -62,10 +99,10 @@ export default function UploadForm({ image, onPress }: Props) {
     uploadImage = useCallback(
         (data: typeof image) => {
             if (!data || !data.data) return
-            
+
             setDiseaseState(null)
             toast.info("Your request is being processed. Please wait a moment.")
-            
+
             const formData = new FormData()
             const file = prepareFileForUpload(data.data, data.name)
             formData.append("image", file)
@@ -74,7 +111,7 @@ export default function UploadForm({ image, onPress }: Props) {
                 .then((data) => {
                     const result = data.data
                     if (!result.status) throw new Error(result.message)
-                        toast.success("You request has been processed.")
+                    toast.success("You request has been processed.")
 
                     const descriptions: {
                         header: string