The Skin Analysis API is a powerful tool that assists skincare professionals and individuals in analyzing their skin's health and identifying potential skin conditions. This API uses advanced image recognition technology to provide multi-dimensional, detailed skin analysis, including the detection and identification of various skin features such as color, smoothness, acne spots, wrinkles, pores, blackheads, dark circles, and eye bags.
The Skin Analysis API is designed to provide comprehensive and accurate results by identifying even the smallest details such as blood vessel dark circles, acne marks, and other imperfections that may not be easily visible to the naked eye. The API's technology works by analyzing high-resolution images of the skin and comparing them to a vast database of skin profiles and conditions to provide an accurate diagnosis.
The Skin Analysis API provides skincare professionals and individuals with the ability to track their skin's health over time. By analyzing changes in the skin's condition, users can identify potential problems early on and take proactive measures to improve their skin's health. Additionally, the API can provide personalized recommendations for skincare products and treatments based on the user's unique skin profile.
Skincare professionals can integrate the Skin Analysis API into their practice, enabling them to provide more accurate diagnoses and tailored treatment plans for their clients. By using the API, skincare professionals can save time and resources by automating the skin analysis process, allowing them to focus on providing high-quality skincare services to their clients.
The Skin Analysis API can also be used in the development of skincare products. By analyzing the efficacy of different ingredients on various skin conditions, skincare companies can develop products that are tailored to their target audience's unique skin profiles. This feature can lead to the development of more effective skincare products that deliver better results for users.
In conclusion, the Skin Analysis API is a valuable tool for skincare professionals, individuals, and skincare companies alike. The API's advanced image recognition technology provides comprehensive and accurate skin analysis, enabling users to identify potential skin problems early on and take proactive measures to improve their skin's health. The Skin Analysis API can also save time and resources for skincare professionals and companies while leading to the development of more effective skincare products.
Pass the image that you want to analyze. Just 1 face per request. Receive an extensive analysis of the located skin imperfections.
Personalized Skincare Recommendations: Skincare companies can use the Skin Analysis API to provide personalized skincare recommendations to their customers. By analyzing the customer's skin profile, the API can suggest products that are tailored to their unique needs and concerns, improving the customer's overall experience and satisfaction.
Skin Health Tracking: Individuals can use the Skin Analysis API to track their skin health over time. By regularly analyzing their skin's condition, users can identify potential problems early on and take proactive measures to improve their skin's health.
Dermatology Diagnosis: Dermatologists can use the Skin Analysis API to assist in diagnosing various skin conditions accurately. The API's advanced image recognition technology can help identify subtle changes in the skin, leading to more accurate diagnoses and treatment plans.
Skincare Product Development: Skincare companies can use the Skin Analysis API to develop new skincare products that are tailored to specific skin profiles and conditions. By analyzing the efficacy of different ingredients on various skin types, companies can create more effective products that deliver better results for their customers.
Beauty Consultations: Skincare professionals can use the Skin Analysis API to provide more accurate and personalized beauty consultations to their clients. By analyzing the client's skin profile, the professional can recommend skincare products and treatments that are tailored to the client's unique needs and concerns, improving the client's overall experience and satisfaction.
Overall, the Skin Analysis API has a wide range of potential use cases that can help improve the quality of skincare products and services provided to customers. By providing accurate and personalized skin analysis, the API can help individuals and professionals alike make better-informed decisions regarding their skincare needs and concerns.
Besides the number of API calls, there are no other limitations.
JPG
, PNG
, BMP
.Provides multi-dimensional detailed skin analysis on the skin, comprehensive detection and identification of skin color, skin smoothness, acne spots, wrinkles, pores, blackheads, dark circles and eye bags, etc., accurate to such as blood vessel dark circles, acne marks, etc. detail
Response Parameters | Type | Description |
---|---|---|
face_num | int | Number of faces in the picture |
face_list | array | List of face information |
face_token | string | Face logo |
location | array | Position of the face in the picture |
+left | double | Distance of the face area from the left border |
+top | double | Distance of the face area from the upper boundary |
+width | double | Width of the face area |
+height | double | Height of the face area |
+degree | int | Clockwise rotation angle of the face frame relative to the vertical direction [-180,180] |
skin | array | Skin related information |
+color | int | Skin tone grading (1-6, lower values indicate lighter skin tone) |
+smooth | int | Skin smoothness grading (1-4, lower values indicate smoother skin) |
acnespotmole | array | Information about mole spots |
+acne_num | int | Number of acne detected |
+acne_list | array | Acne list |
++type | int | Acne type (0: Whitehead, 1: Acne mark, 2: Pustules, 3: Nodules) |
++score | double | Confidence range for this area (0-1) |
++left | double | Distance between the left border of the acne area and the picture's left border |
++top | double | Distance between the upper border of the acne area and the picture's upper border |
++right | double | Distance between the right border of the acne area and the picture's left border |
++bottom | double | Distance between the bottom border of the acne area and the picture's upper border |
+speckle_num | int | Number of spots |
+speckle_list | array | Spot information list |
++type | int | Spot type (0: chloasma, 1: freckles, 2: sunburn, 3: age spots) |
++score | double | Confidence range for this area (0-1) |
++left | double | Distance between the left border of the spot area and the picture's left border |
++top | double | Distance between the upper border of the spot area and the picture's upper border |
++right | double | Distance between the right border of the spot area and the picture's left border |
++bottom | double | Distance between the bottom border of the spot area and the picture's upper border |
+mole_num | int | Number of moles |
+mole_list | array | Mole information list |
++score | double | Confidence range for moles (0-1) |
++left | double | Distance between the left border of the mole area and the picture's left border |
++top | double | Distance between the upper border of the mole area and the picture's upper border |
++right | double | Distance between the right border of the mole area and the picture's left border |
++bottom | double | Distance between the bottom border of the mole area and the picture's upper border |
wrinkle | array | Wrinkle information |
+wrinkle_num | int | Number of wrinkles |
+wrinkle_types | int | Wrinkle types (1: forehead wrinkles, 2: Sichuan-shaped lines, 3: fine lines around the eyes, 4: crow’s feet, 5: nasolabial lines, 6: wrinkles around the mouth) |
+wrinkle_data | array | Wrinkle information |
++x | double | Distance from the wrinkle point to the left border |
++y | double | Distance between the wrinkle point and the upper boundary |
eyesattr | array | Eye attribute information |
+dark_circle_left_type | int | Types of dark circles in the left eye (0: pigment type, 1: shadow type, 2: vascular type) |
+dark_circle_right_type | int | Types of dark circles in the right eye (0: pigment type, 1: shadow type, 2: vascular type) |
+dark_circle_left | array | Dark circles on the left eye |
+++x | double | Distance of the dark circle from the left border |
+++y | double | Distance of the dark circle from the upper boundary |
+dark_circle_right | array | Dark circles on the right eye |
+++x | double | Distance of the dark circle from the left border |
+++y | double | Distance of the dark circle from the upper boundary |
+eye_bags_left | array | Left eye bag |
+++x | double | Distance of the eye bag from the left border |
+++y | double | Distance between the bags under the eyes and the upper boundary |
+eye_bags_right | array | Right eye bag |
+++x | double | Distance of the eye bag from the left border |
+++y | double | Distance between the bags under the eyes and the upper boundary |
+eye_bags_left_type | array | Left eye bag type (1: Fat type, 2: Tear groove type, 3: Mixed type) |
+eye_bags_right_type | array | Types of bags under the right eye (1: Fat type, 2: Tear groove type, 3: Mixed type) |
blackheadpore | array | Blackhead pore information |
+poly | array | Areas where blackhead pores are detected |
++class_id | int | Blackhead or pore identification (0 means blackhead, 1 means pore) |
++score | double | Probability (0-1) |
++left | double | Location of the left boundary of the area |
++right | double | Location of the right boundary of the area |
++top | double | Location of the upper boundary of the area |
++bottom | double | Location of the lower boundary of the area |
++point | array | Outer contour points of pores or blackheads |
+++x | double | Distance of the pore or blackhead from the left border |
+++y | double | Distance of the pores or blackheads from the upper boundary |
circles | array | Center point and radius of pores or blackheads |
+++blackhead | array | Center point and radius of all blackheads |
++++x | double | Distance from the center point of the black head to the left boundary |
++++y | double | Distance from the center point of the black head to the upper boundary |
++++r | double | Blackhead radius |
+++pore | array | Center point and radius of all pores |
+++++x | double | Distance between the center point of the pore and the left boundary |
+++++y | double | Distance between the center point of the pore and the upper boundary |
+++++r | double | Pore radius |
+pore_num | int | Number of pores |
+pore_segs_type | array | Pore type (1: oily type, 2: dehydrated type, 3: keratinous type |
Object | Description |
---|---|
max_face_num |
[Required] |
face_field |
[Required] |
Request Body |
[Required] File Binary |
{"Example Response":"No response example available for now."}
curl --location 'https://zylalabs.com/api/1991/skin+analysis+api/1755/get+analysis?max_face_num=1&face_field=color,smooth,acnespotmole' \
--header 'Content-Type: multipart/form-data' \
--form 'image=@"FILE_PATH"'
After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Skin Analysis API REST API, simply include your bearer token in the Authorization header.
Header | Description |
---|---|
Authorization
|
[Required] Should be Bearer access_key . See "Your API Access Key" above when you are subscribed. |
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