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[update] add process for single and multiple image

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NatLee 2025-01-07 04:56:05 +08:00
parent 36fb512bec
commit 431544ac52
1 changed files with 32 additions and 8 deletions
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30
deepface/modules/demography.py
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@ -183,14 +183,22 @@ def analyze(
model = modeling.build_model(task="facial_attribute", model_name="Emotion")
emotion_predictions = model.predict(faces_array)
# Handle single vs multiple emotion predictions
if len(emotion_predictions.shape) == 1:
# Single face case - reshape predictions to 2D array for consistent handling
emotion_predictions = emotion_predictions.reshape(1, -1)
# Process predictions for each face
for idx, predictions in enumerate(emotion_predictions):
sum_of_predictions = predictions.sum()
resp_objects[idx]["emotion"] = {}
# Calculate emotion probabilities and store in response
for i, emotion_label in enumerate(Emotion.labels):
emotion_prediction = 100 * predictions[i] / sum_of_predictions
resp_objects[idx]["emotion"][emotion_label] = emotion_prediction
emotion_probability = 100 * predictions[i] / sum_of_predictions
resp_objects[idx]["emotion"][emotion_label] = emotion_probability
# Store dominant emotion
resp_objects[idx]["dominant_emotion"] = Emotion.labels[np.argmax(predictions)]
elif action == "age":
@ -198,14 +206,25 @@ def analyze(
model = modeling.build_model(task="facial_attribute", model_name="Age")
age_predictions = model.predict(faces_array)
# Handle single vs multiple age predictions
if len(age_predictions.shape) == 1:
# Single face case - reshape predictions to 2D array for consistent handling
age_predictions = age_predictions.reshape(1, -1)
for idx, age in enumerate(age_predictions):
resp_objects[idx]["age"] = int(age)
resp_objects[idx]["age"] = np.argmax(age)
elif action == "gender":
# Build the gender model
model = modeling.build_model(task="facial_attribute", model_name="Gender")
gender_predictions = model.predict(faces_array)
# Handle single vs multiple gender predictions
if len(gender_predictions.shape) == 1:
# Single face case - reshape predictions to 2D array for consistent handling
gender_predictions = gender_predictions.reshape(1, -1)
# Process predictions for each face
for idx, predictions in enumerate(gender_predictions):
resp_objects[idx]["gender"] = {}
@ -220,6 +239,11 @@ def analyze(
model = modeling.build_model(task="facial_attribute", model_name="Race")
race_predictions = model.predict(faces_array)
# Handle single vs multiple race predictions
if len(race_predictions.shape) == 1:
# Single face case - reshape predictions to 2D array for consistent handling
race_predictions = race_predictions.reshape(1, -1)
for idx, predictions in enumerate(race_predictions):
sum_of_predictions = predictions.sum()
resp_objects[idx]["race"] = {}