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detect.py

@@ -52,46 +52,9 @@ class DengueDetector:
         print("Modelo carregado com as seguintes classes:", self.names)
 
     def calculate_intensity(self, objects):
-        if not objects:
-            return 0.0
-        
-        weights = {
-            "piscina_suja": 10.0,
-            "reservatorio_de_agua": 8.0,
-            "pneu": 6.0,
-            "lona": 4.0,
-            "monte_de_lixo": 3.0,
-            "saco_de_lixo": 2.0,
-            "piscina_limpa": 1.0
-        }
-        
-        total_score = 0.0
-        first_obj = objects[0]
-        img_w = first_obj["box"]["original_width"]
-        img_h = first_obj["box"]["original_height"]
-        total_img_area = float(img_w * img_h)
-
-        if total_img_area == 0:
-            for obj in objects:
-                weight = weights.get(obj["class"], 1.0) 
-                confidence = obj["confidence"]
-                total_score += weight * confidence
-            return total_score
-
-        for obj in objects:
-            weight = weights.get(obj["class"], 1.0) 
-            confidence = obj["confidence"]
-            
-            box = obj["box"]
-            w = box["x2"] - box["x1"]
-            h = box["y2"] - box["y1"]
-            obj_area = w * h
-            relative_area = obj_area / total_img_area
-            
-            risk_contribution = weight * confidence * relative_area
-            total_score += risk_contribution
-        
-        return total_score 
+        weights = {"piscina": 9, "caixa_agua": 4}
+        score = sum(weights.get(obj["class"], 0) for obj in objects)
+        return score
 
     def detect_image(self, image_bytes, fast: bool = True):
         img = Image.open(BytesIO(image_bytes)).convert("RGB")
@@ -196,10 +159,6 @@ class DengueDetector:
                 x2 *= inv
                 y2 *= inv
             cname = self.names[int(c)]
-
-            if cname == "lona" and s < 0.6:
-                continue
-
             class_names.append(cname)
             detections.append({
                 "class": cname,
@@ -218,4 +177,4 @@ class DengueDetector:
             "contagem": counts,
             "objetos": detections,
             "intensity_score": intensity_score
-        }
+        }

predict.py

@@ -249,4 +249,4 @@ class DenguePredictor:
             {"factor": "Humidity", "value": "Increases adult mosquito survival"}
         ]
 
-        return lag_plot_b64, summary, tipping_points
+        return lag_plot_b64, summary, tipping_points